Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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Assessment of the social capital impact on the household income of the Russian Federation regions by N. Е. Karmanova, A. V. Koritskiy

“…The authors propose a methodological approach that distinguishes the study from other economists – this is mathematical modeling using the extended Cobb-Douglas production function with the inclusion of indicators representing human and social capital in the number of independent variables of this function. …”
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Intelligent fault diagnosis of shearer based on simplified interval kernel global-local feature fusion by Ning LI, Hua DING, Xiaochun SUN, Zeping LIU, Guoshu PU

“…The results show that compared with the midpoint-radius kernel PCA, the kernel local preservation projection and interval kernel global-local feature fusion algorithms, the proposed method has a good monitoring effect on the single variable simulation fault, the multi-variable pick loss and the waterway blockage fault of shearers. …”
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Modal Analysis of QP and LP Solution in Steady-state Optimization Layer of Two-layer Structure MPC by WANG Hongrui, ZHANG Xin, LIU Bowen, LIN Na, ZOU Tao

“…Simulation results prove that QP had better continuity than LP when the weight coefficient of decision variables are changed, and the weight coefficient of QP can more accurately adjust the bias of decision variables. …”
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Numerical solutions for fractional optimal control problems using Mü‎‎‎‎‎‎‎ntz-Legendre polynomials by Mohammad Sahabi, Allahbakhsh Yazdani Cherati

“…To achieve this, stable and efficient methods for calculating the fractional integral and derivative operators of Müntz-Legendre functions based on three-term recurrence formulas and Jacobi-Gauss quadrature rules are presented. …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent 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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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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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. …”
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Some Iterative Methods Free from Derivatives and Their Basins of Attraction for Nonlinear Equations by Farahnaz Soleimani, Fazlollah Soleymani, Stanford Shateyi

“…First, we make the Jain's derivative-free method optimal and subsequently increase its efficiency index from 1.442 to 1.587. Then, a novel three-step computational family of iterative schemes for solving single variable nonlinear equations is given. …”
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Dual-Stream Enhanced Deep Network for Transmission Near-Infrared Dorsal Hand Vein Age Estimation with Attention Mechanisms by Zhenghua Shu, Zhihua Xie, Xiaowei Zou

“…Simultaneously, another deep residual network is leveraged to strengthen the representation ability on subtle dorsal vein textures. Moreover, variable activation functions and pooling layers are integrated into the respective streams to enhance the nonlinearity modeling of the dual-stream model. …”
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Pulley ring suture increases shoulder stability after biceps tendon transposition by Duzheng Zhang, Jiezhou Wu, Liyun Zhang, Qiyun Chen, Chao Wang, Ming Cai, Ruijun Cong

“…These statistically significant variables and their coefficients were used to build a generalized linear equation and selected to build the final model including Grouping information (OR:1.61E + 01;95% CI:5.8854–52.5200), Mean T value of bone mineral density (OR:6.95E + 00;95% CI:2.4695–25.6797) and 3 Months post operation UCLA score (OR:1.77E + 00;95% CI:1.4810–2.2539).ConclusionsCompared with the traditional MDBT, the modified MDBT is more effective in improving the long-term function of the glenohumeral joint and better restoring the biological state of the glenohumeral joint.…”
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GDP per capita vs foreign direct investment: key drivers of a country's technological leadership by Aleksy Kwilinski

“…A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. …”
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Nonlinearity Estimation and Compensation for Accurate PMSM Modeling and Voltage Prediction by Beichen Ding, Yuting Lu, Chunyan Lai, Weiwen Peng, Kaide Huang, Guodong Feng

“…Specifically, the offsets to the base model are modeled using nonlinear functions with variable coefficients to compensate saturation and core loss effect, which can achieve better accuracy without changing the model structure. …”
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Inference of Impulse Responses via Bayesian Graphical Structural VAR Models by Daniel Felix Ahelegbey

“…Impulse response functions (IRFs) are crucial for analyzing the dynamic interactions of macroeconomic variables in vector autoregressive (VAR) models. …”
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Evaluating the Effectiveness of Quality Control Measures in Project Management: A Study of Construction Companies in Lusaka by Mwanza Jacob, Chimbomba Kelvin

“…A solid positive relationship appeared between how well technology supports quality control and general quality control practices (Pearson coefficient = 0.893). Quality control measures improve the efficiency of construction projects, but they should be further improved as many projects still get delayed as a result of quality issues. …”
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Modelagem da produtividade e gestão da qualidade acadêmica by Annibal Parracho Sant'Anna

“…It is a hierarchical model because technical coefficients of the academic production function are modeled as function of second level explanatory variables in such a way that such production function is allowed to change coherently from one department to another. …”
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Path following control of underground mining articulated vehicle based on the preview control method by MENG Yu, GAN Xin, BAI Guo-xing

“…By considering the relationship between the position and situation of the vehicle, the objective function of the predictive control was optimized by minimizing the lateral deviation of the following path and the heading angle deviation of the vehicle. …”
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Bivariate Epanechnikov-exponential distribution: statistical properties, reliability measures, and applications to computer science data by H. M. Barakat, M. A. Alawady, I. A. Husseiny, M. Nagy, A. H. Mansi, M. O. Mohamed

“…The statistical properties of the EP-EX-FGM model are examined, including product moments, coefficient of correlation between the internal variables, moment generating function, conditional distribution, concomitants of order statistics (OSs), mean residual life function, and vitality function. …”
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A secondary analysis of gait after a 4-week postural intervention for older adults with hyperkyphosis by L. C. Hughes, A. L. Ellis, H. L. Rogers, M. Hadley, R. V. Galloway

“…Pearson correlation coefficients were utilized to investigate correlations between all variables at baseline and in pre- and post intervention change values. …”
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