Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…SCR model estimates of abundance, the density-covariate coefficient β and the movement-related scale parameter of the detection function σ were robust to ignoring temporal variation in detection, with relative bias, CV and RMSE of the two models generally being within 4% of each other. …”
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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Some comments on the assessment of students’ knowledge at the University by Darya I. Yareshchenko

“…The parametric approach consists in choosing the form of the function up to a vector of parameters and the subsequent evaluation of these coefficients by a training sample. …”
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HEART AND VESSEL REMODELING IN DIFFERENT AGE GROUPS OF PATIENTS WITH ARTERIAL HYPERTENSION by V. N. Kandilova

“…The Spearman rank correlation coefficient (r) was used to estimate the relationship between these variables. …”
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A Low-Complexity Direction-of-Arrival Estimation Algorithm for Noncircular Signals via Subspace Rotation Technique by Wei Wang, Ming Zhang, Bobin Yao, Tongxing Zheng, Xiaojiao Fan

“…Then, utilizing the separation of variables and the orthogonality between the reduced-dimension noise subspace and the space spanned by the columns of the extended manifold matrix, a new one-dimensional spectral search function is derived to estimate DoAs. …”
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Empirical Study of the Impact of Unemployment on Political Stability in Iran (1985-2015) by habib samani, robabeh khilkordi

“…Vector regression (VAR), Johansson-Juselius, Vector Error Correction Model (VECM), and variance analysis function were used for this purpose. The results show that in the long run, two variables of unemployment rate and Gini coefficient have a negative and significant relationship with political stability. …”
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A novel unified variational finite difference (VFD) solution method for optimal control problems by Amir Norouzzadeh, Nader Nariman-zadeh, Reza Ansari

“…To do so, the general form of quadratic performance index function and nonlinear state equations are considered first. …”
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Pedestrian detection method based on improved YOLOv5 by Shangtao You, Zhenchao Gu, Kai Zhu

“…We optimize the regression prediction of the anchor using the Efficient IOU Loss (EIOU) function. Experimental data show that the mean average precision (mAP) of the HOD-YOLOv5 model achieves 83.5%, compared to YOLOv5, which is 4.4% higher than original YOLOv5, and the recognition speed of the HOD-YOLOV5 reaches 106.7 frames per second (FPS). …”
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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…The increase of groove parameters (groove width and depth) can enhance the contact pressure, and at the same time, increase the equivalent stress, which may lead to local strength deficiency.Through the sensitivity analysis, the sensitivity coefficients of the radius of the metal seal ring to the equivalent force and contact pressure were found to reach 0.67 and 0.82, which were the dominant variables affecting the sealing performance; the width and depth of the grooves regulated the stress distribution through the geometric compensation mechanism. …”
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Decomposed Linear Dynamical Systems (dLDS) models reveal instantaneous, context-dependent dynamic connectivity in C. elegans by Eva Yezerets, Noga Mudrik, Adam S. Charles

“…Abstract Mounting evidence indicates that neural “tuning” can be highly variable within an individual across time and across individuals. …”
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Order assignment mechanism based on hierarchical decomposition and element matching by ZHANG Xinyue, LYU Weimin, WEI Dingjiang, YANG Dongsheng

“…This integrates and coordinates operational tasks, ensures no resource conflicts, and provides alternatives for responding to battlefield variables. The approach employs a planning network model to illustrate the logical interrelationships among operations. …”
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Exploring the Impact of School-Based Physical and Perceived Environments on Students’ Physical Activity During Recess: A Case Study of Four Schools in Xi’an, China by Qing Wang, Yan Wang, Lan Zhou, Yong Nan

“…The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. …”
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Well Placement Optimization for Fractured Reservoirs: Coupling StoSAG and EDFM by Jianchun Xu, Wanhang Guo, Wenxin Zhou

“…Well placement optimization is a significant task in oil field development which aims to find the optimal well locations by maximizing the net present value (NPV) or other objective function. It is a highly nonlinear problem involving large number of variables. …”
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Reliability-Based Topology Optimization Considering Overhang Constraints for Additive Manufacturing Design by Fahri Murat, Irfan Kaymaz, Abdullah Tahir Şensoy

“…RBTO addresses uncertainties in design variables to enhance reliability. This research investigates build direction parameter solutions using deterministic and RBTO algorithms. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

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Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…The reward function integrates multiple objectives, including safety, fuel consumption, and traffic efficiency. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…The predicted data were evaluated by computing the correlation coefficients and area under the curve (AUC). Results: As a numerical variables analysis, albumin and hemoglobin predictions were relatively accurate (R=0.71, 0.74). …”
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Optimization by RSM of reinforced concrete domes with meridian ribs, under static loading. by Logzit N., Raouache E., Bentoumi M., Bentoumi A., Khababa I.

“…Ultimately, a cost-oriented objective function is derived, incorporating a load-bearing capacity coefficient. …”
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