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Publications - 6383

Straw mulching optimized the root and canopy structure of soybean by reducing the topsoil temperature before blooming period

Cunxiang Wu Simon Willcock Viktoria Vona Robert Dunn Wenwen Song Qirui Li Cailong Xu A. Vér Ruidong Li Zongsheng Wu Jianxin Hua Yifan Xu Yupeng Zhu Qirui Li Yifan Xu

Publication Name: Field Crops Research

Publication Date: 2025-11-01

Volume: 333

Issue: Unknown

Page Range: Unknown

Description:

Context: The soybean seed yield in the Huang-Huai-Hai (HHH) region is challenged by high temperatures before blooming. Straw mulching can act to reduce topsoil temperature. However, little is known about whether changes in topsoil temperature contribute to the optimization of soybean root and canopy structure and, ultimately, yield. Objective: The aim of this study is to investigate the effects of straw mulching on soybean topsoil temperature, root growth, and canopy structure in the HHH region, China. Methods: A randomized block design was adopted (2020–2023) in the field, including three straw treatments: straw removing (SR), straw mulching (SM), and straw crushing (SC). Topsoil temperature, root morphology, leaf area index (LAI), light transmittance, canopy photosynthesis, dry matter accumulation, and seed yield of soybean under different treatments were measured. Furthermore, the test results were validated by pot experiment (LT: topsoil cooling, CT: topsoil non-cooling) in 2024. Results: Before soybean blooming, the highest topsoil temperature was 28.47℃ in SR, followed by 27.47℃ in SC and 26.95℃ in SM. Compared to SR and SC, the root length, root surface area, root volume and root dry weight of SM increased by an average of 26.04 %, 27.79 %, 29.13 % and 38.82 %, respectively. Soybean root dry matter weight was significantly positively correlated (P < 0.01) with the LAI and above-ground dry matter accumulation. Compared to SR and SC, Fv/Fm, Y(II), and ETR under SM treatment increased by 8.38 %, 7.94 %, and 7.73 %, respectively. Y(II) of the LT treatment was also significantly (P < 0.05) increased by 17.53 % compared to CT. Among the three treatments, soybean canopy photosynthetic rate and seed yield under SM treatment were, on average, significantly increased by 9.97 %, and 11.87 %, respectively. Furthermore, we identified the LAI characteristics of high-yield soybean canopy: 2.22 0.62 in the lower layer. Conclusion and implications: These findings imply that regulating topsoil temperature through straw mulching optimizes root and canopy development, improving soybean yield. This study provides insights into mitigating heat stress and enhancing sustainable soybean production in warm climates.

Open Access: Yes

DOI: 10.1016/j.fcr.2025.110067

Method for determining direction, velocity and position of a flying ball

A. Nagy

Publication Name: Mechatronics 2013 Recent Technological and Scientific Advances

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: 401-408

Description:

This paper proposes an algorithm for an optical measuring system, which is capable of calculating the velocity and position components, the radius and the trajectory of a flying sphere-shape ball. The infrared light-emitting diodes and the IR sensors of the system are arranged in a single plane and create a lattice of infrared light beams. The FPGA based hardware of the system measures the points in time when the light beams are interrupted by the ball. The proposed algorithm uses the measured time-data with the associated positions of the interrupted light beams as input. The practical application such a systems can be measuring ball's velocity in several sports and games. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-02294-9_51

A Novel Tree-Seed Teaching Learning based optimization Algorithm for constrained optimization problems

Dragan Pamucar Sarika Jain Parvesh Kumar None Aanchal

Publication Name: Systems and Soft Computing

Publication Date: 2026-06-01

Volume: 8

Issue: Unknown

Page Range: Unknown

Description:

Nature-inspired algorithms have proven invaluable in addressing complex, non-linear and non-convex optimization problems. Combining two or more strategies can improve accuracy, adaptability, and efficiency in tackling complex problems while efficiently dealing with uncertainties and nonlinearity. In this research, we present a hybrid approach known as Tree-Seed Teaching Learning based Optimization algorithm (TSTLBO), in which the teaching phase of Teaching Learning based Optimization (TLBO) algorithm is modified by the seeds generation approach of the Tree seed algorithm (TSA) to increase problem-solving skills. TLBO's exploration capabilities are limited. Keeping this in mind, we combined TLBO and the TSA algorithm to take advantage of both in a single variant, resulting in improved performance when addressing complex optimization problems. The proposed hybrid algorithm has better capability to escape from local optima with faster convergence than the standard TLBO and TSA. The performance of the proposed hybrid approach was evaluated against 30 IEEE CEC-2017 (IEEE Congress on Evolutionary Computation 2017) benchmark functions of varied complexity and structural design problems. The computed results are compared to numerous existing state-of-the-art studies. Experimental findings reveal that the proposed TSTLBO outperforms other existing algorithms. Among the 30 benchmark functions, TSTLBO achieves superior results on 25 and gives same values for 2 functions for dimension 10, whereas for dimension 30, the proposed algorithm performs better on 18 and gives equal values for 4 functions. Furthermore, the TSTLBO results are evaluated using the statistical analysis test. Among four real-life problems, TSTLBO ranked first.

Open Access: Yes

DOI: 10.1016/j.sasc.2026.200491

A dynamic programming approach for 4D flight route optimization

Gabor Takacs Christian Kiss-Toth

Publication Name: Proceedings 2014 IEEE International Conference on Big Data IEEE Big Data 2014

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: 24-28

Description:

This paper describes our solution for the GE Flight Quest 2 (FQ2) challenge, organized by Kaggle. FQ2 aimed at optimizing flight routes so that the overall cost depending on fuel consumption and delay is as low as possible. The contestants could use several data tables as inputs, including aircraft positions and destinations, weather information and other aviation related data. Their task was to produce a flight plan for each flight, given as a list of (latitude, longitude, altitude, airspeed) quadruplets. The cost of the flight plans was evaluated with an open source simulator. Our proposed method produces an initial solution with the Dijkstra's algorithm to avoid restricted zones, and then refines it using dynamic programming and local search techniques. We can extensively utilize wind forecasts and significantly divert the planes from the the great circle route if necessary. Moreover, our method tries to set the ascending and descending profiles of the flights to further decrease the cost. Our algorithm achieved second place on the public, and fifth place on the private leaderboard of the contest.

Open Access: Yes

DOI: 10.1109/BigData.2014.7004427

Coping strategies for financial problems: Based on Hungarian data from the OECD 2022 annual report

Németh Erzsébet Botond Géza Kálmán Szonja Jenei Szilárd Malatyinszki

Publication Name: International Journal of Innovative Research and Scientific Studies

Publication Date: 2025-01-01

Volume: 8

Issue: 4

Page Range: 407-418

Description:

The aim of this study is to explore the role of demographic factors in strategies to address financial problems, based on data from the OECD Financial Literacy Survey 2022 in Hungary. The analysis focused on differences in age, gender, type of residence, income, and region. The research used multivariate statistical methods, such as canonical correlation analysis and Ridge regression, to identify associations between demographic factors and financial behavior. The results showed that region and age are the most significant determinants of financial strategy choice, while education and income have a smaller impact. Residents in Budapest showed higher financial awareness and more diversified strategies compared to a more traditional approach for rural residents. The results suggest the development of targeted financial education programs that take demographic and regional differences into account, thus supporting the enhancement of financial stability.

Open Access: Yes

DOI: 10.53894/ijirss.v8i4.7861

Prediction system of rolling contact fatigue on crossing nose based on support vector regression

Szabolcs Fischer Mykola Sysyn Olga Nabochenko Jianxing Liu Wei He Lei Kou

Publication Name: Measurement Journal of the International Measurement Confederation

Publication Date: 2023-03-31

Volume: 210

Issue: Unknown

Page Range: Unknown

Description:

It is essential to assess the rolling contact fatigue (RCF) of turnouts and maintain them in advance. It saves a lot of money while protecting the safety of railway operations. In Germany, the damage on rails, especially crossing noses, mainly depends on the subjective judgment of experts. There are no objective and comprehensive evaluation criteria. This paper presents the application of image processing and supervised machine learning algorithms to crossing nose fatigue judgment. The fatigue characteristics of the crossing nose rolling contact surface along the life cycle of the crossing nose are analyzed. The study used crack information from magnetic particle inspection (MPI) images of crossing nose surfaces. It uses basic image processing methods to collect physical information about features of fatigue cracks in images. Existing feature selection methods are used to exclude irrelevant features and retain valuable features. And we select the best feature selection method through the regression results. Statistically significant crack features and combinations that depict the surface fatigue state are found. In this paper, by comparing several usually machine learning regression algorithms, it is found that the supervised learning of support vector machine regression (SVR) has achieved the best results in the regression fitting of the crack feature data in this paper. The regression results form a simple system to evaluate the life cycle of crossing nose. The system finds the location of cracks that can create dangerous defects in the crossing nose surface. The research result consists of the early prediction of rail contact fatigue.

Open Access: Yes

DOI: 10.1016/j.measurement.2023.112579

Tensor Product Transformation Based Robust Control of Induction Machine

Miklós Kuczmann Zoltan Nemeth

Publication Name: Gpmc 2020 2nd IEEE International Conference on Gridding and Polytope Based Modeling and Control Proceedings

Publication Date: 2020-11-19

Volume: Unknown

Issue: Unknown

Page Range: 39-44

Description:

The paper presents the tensor product based model of the highly nonlinear induction machine model. The independence of flux and speed state feedback control has been examined with integral action. Robustness of the designed controller has been investigated with applied load torque, additional measurement noise and parameter uncertainties.

Open Access: Yes

DOI: 10.1109/GPMC50267.2020.9333812

Complex analysis of the dynamic effects of car population along the trajectories

T. Péter Ferenc Szauter József Bokor

Publication Name: Proceedings of the ASME Design Engineering Technical Conference

Publication Date: 2015-01-01

Volume: 9

Issue: Unknown

Page Range: Unknown

Description:

The analyses apply new complex model to analyze both road traffic transport processes and spatial nonlinear vehicle dynamic effects. Therefore also the network traffic processes can be analyzed and in a united system the spatial vehicle dynamic processes realized on networks can be attained. Objective the raising the dynamic safety, risk and hazard analysis, reducing the environmental impact of vehicles.

Open Access: Yes

DOI: 10.1115/DETC2015-47075

Anthropometric Determinants of Rowing Performance in a Multinational Youth Cohort

Ferenc Ihász László Suszter Ottó Benczenleitner Zoltán Gombos Zoltán Alföldi

Publication Name: Journal of Functional Morphology and Kinesiology

Publication Date: 2026-03-01

Volume: 11

Issue: 1

Page Range: Unknown

Description:

Background: Rowing performance in youth athletes is strongly influenced by anthropometric characteristics, body composition, and limb proportions; however, the combined contribution of these factors across developmental stages remains insufficiently understood. This study investigated the relationships between key anthropometric variables and ergometer performance in a multinational cohort of young rowers. Methods: A total of 194 athletes (48 females, 146 males) from ten countries participated. Based on age and sex, participants were categorized into junior female (JF), junior male (JM), adult female (AF), and adult male (AM) groups. Body height, body mass, body fat (F%), relative muscle mass (M%), limb lengths, and body surface area (BSA) were measured. Rowing performance was assessed via maximal 2000 m ergometer trials. Results: Males outperformed females across all age groups (p < 0.001). Performance showed strong positive correlations with body height (r = 0.673, p = 0.003), body mass (r = 0.724, p = 0.005), arm span (r = 0.681, p = 0.002), lower-limb length (r = 0.394, p = 0.004), relative muscle mass (39.9 ± 5.2%; r = 0.531, p < 0.001), and especially BSA (1.94 ± 0.19 m2; r = 0.739, p < 0.001). Relative body fat was negatively associated with performance (17.6 ± 6.9%; r = −0.465, p < 0.001). Conclusions: Findings indicate that rowing performance in youth athletes reflects multidimensional anthropometric configurations rather than isolated traits, characterized primarily by the combined contribution of body surface area, relative muscle mass, and segmental body dimensions. From a practical perspective, higher-performing athletes typically exhibited body surface area values approaching or exceeding ~1.90 m2 and relative muscle mass above ~40%, suggesting these ranges as indicative reference benchmarks rather than fixed selection thresholds. Integrating anthropometric profiling with physiological assessment may enhance early talent identification and support individualized training strategies in competitive youth rowing.

Open Access: Yes

DOI: 10.3390/jfmk11010039