Dynamic Gesture Recognition Algorithm Combining Global Gesture Motion and Local Finger Motion for Interactive Teaching by Li Jiashan, Li Zhonghua

“…Adding dynamic gesture recognition to the new interactive teaching system is of great significance to improve the teaching efficiency. However, the features extracted by traditional dynamic gesture recognition methods are usually difficult to accurately represent the differences between dynamic gestures. …”
Get full text

Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
Get full text

Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…All ML algorithms showed varied efficiencies in predicting the nonlinear relationships among parameters, with higher efficiency in predicting the behavior of root and shoot dry mass, root fresh weight and number of flowers according to R2 index. …”
Get full text

Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
Get full text

Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
Get full text

Flow-based cytometric analysis of cell cycle via simulated cell populations. by M Rowan Brown, Huw D Summers, Paul Rees, Paul J Smith, Sally C Chappell, Rachel J Errington

“…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
Get full text

A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
Get full text

A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
Get full text

Optimal power flow using recent red-tailed hawk optimization algorithm by Ahmed M Nassef, Mohammad Ali Abdelkareem, Mohamed Louzazni

“…Optimization can efficiently achieve various objective functions in power systems. …”
Get full text

Reference Intervals for Echocardiography Parameters of Children Living in the Arkhangelsk Region and a Digital Application for Their Assessment by Aleksey A Karyakin, Igor’ S. Chub, Ol’ga E. Karyakina, Andrey M. Grjibovski, Aleksey V. Artemov, Ul’yana R. Zakharchenko

“…Reference intervals of echocardiography parameters were determined using body surface area as the dependent variable. The values were automatically calculated in our digital application that allows one to increase the accuracy and efficiency of interpretation of cardiac ultrasound parameters. …”
Get full text

Expanding a Health Technology Solution to Address Therapist Challenges in Implementing Homework With Adult Clients: Mixed Methods Study by Brian E Bunnell, Kaitlyn R Schuler, Julia Ivanova, Lea Flynn, Janelle F Barrera, Jasmine Niazi, Dylan Turner, Brandon M Welch

“… BackgroundHomework is implemented with variable effectiveness in real-world therapy settings, indicating a need for innovative solutions to homework challenges. …”
Get full text

Impact of IgG subclass on monoclonal antibody developability by Paul Cain, Lihua Huang, Yu Tang, Victor Anguiano, Yiqing Feng

“…We thus conducted a systematic study of 12 mAbs derived from three sets of unrelated variable regions, each cloned into IgG1, an IgG1 variant with diminished effector functions, IgG2, and a stabilized IgG4 variant with further reduced FcγR interaction, to evaluate the impact of IgG subclass on manufacturability and high concentration stability in a common formulation buffer matrix. …”
Get full text

Evaluating the Effectiveness of Quality Control Measures in Project Management: A Study of Construction Companies in Lusaka by Mwanza Jacob, Chimbomba Kelvin

“…Quality control measures implemented in project management functions of construction companies function as essential elements which support project achievement, client fulfillment, and business endurance. …”
Get full text

Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework by Yuyan Annie Pan, Jifu Guo, Yanyan Chen, Siyang Li, Wenhao Li

“…The model-driven method is commonly used to solve TSE efficiently and calibrate the parameters of these models. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Sensitivity Analysis of the Thermal Structure Within Subduction Zones Using Reduced‐Order Modeling by Gabrielle M. Hobson, Dave A. May

“…Our analysis highlights the strong effect of variability in the apparent coefficient of friction, with previously published ranges resulting in pronounced variability in estimated rupture limit depths.…”
Get full text

Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

“…The functional and mechanical properties of the gelatin depend on the chemical and structural characteristics. …”
Get full text

The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…Prediction ability of bed load transport is variable due to complexities that governs fluvial sediment transport in different flow conditions. …”
Get full text

Predictive model of small choroidal melanoma progression after eye-saving treatment based on clinical, morphometric and immunological parameters by E. B. Myakoshina, I. G. Kulikova, N. V. Balatskaya, L. A. Katargina, S. V. Saakyan

“…A formula was calculated where P (z) is the value of the logistic function; Z, linear combination of symptoms; bo , intercept (free term), bi – regression coefficients for parameters Zi.P (z) = 1 : 1 + e – b0– b1z1– b2z2– b3z3– b4z4The logistic function increases monotonically and takes the values from 0 to 1 for any b and Z values [P∈ (0;1)]. …”
Get full text