Search Results (5,312)

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l₁ and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction d_s is influenced by the initial seeding potato’s speed $v_{0t}$, dropping height h_s, and the angle between the seeding pipe and the horizontal ground β_s. The horizontal moving distance x_r of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground β_s2, the distance from its centroid to the reseeding door d, and the dropping height of the potato h_r. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices. Full article

Uncertain differential equations, as an alternative to stochastic differential equations, have proved to be extremely powerful across various fields, especially in finance theory. The issue of parameter estimation for uncertain differential equations is the key step in mathematical modeling and simulation, which is very difficult, especially when the corresponding terms are driven by some complicated uncertain processes. In this paper, we propose the uncertainty counterpart of the threshold Ornstein–Uhlenbeck process in probability, named the uncertain threshold Ornstein–Uhlenbeck process, filling the gaps of the corresponding research in uncertainty theory. We then explore the parameter estimation problem under different scenarios, including cases where certain parameters are known in advance while others remain unknown. Numerical examples are provided to illustrate our method proposed. We also apply the method to study the term structure of the U.S. Treasury rates over a specific period, which can be modeled by the uncertain threshold Ornstein–Uhlenbeck process mentioned in this paper. The paper concludes with brief remarks and possible future directions. Full article

Knowledge-aware recommendation systems have shown superior performance by connecting user item interaction graph (UIG) with knowledge graph (KG) and enriching semantic connections collected by the corresponding networks. Among the existing methods, self-supervised learning has attracted the most attention for its significant effects in extracting node self-discrimination auxiliary supervision, which can largely improve the recommending rationality. However, existing methods usually employ a single (either node or edge) perspective for representation learning, over-emphasizing the pair-wise topology structure in the graph, thus overlooking the important semantic information among neighborhood-wise connection, limiting the recommendation performance. To solve the problem, we propose Hierarchical self-supervised learning for Knowledge-aware Recommendation (HKRec). The hierarchical property of the method is shown in two perspectives. First, to better reveal the knowledge graph semantic relations, we design a Triple-Graph Masked Autoencoder (T-GMAE) to force the network to estimate the masked node features, node connections, and node degrees. Second, to better align the user-item recommendation knowledge with the common knowledge, we conduct contrastive learning in a hybrid way, i.e., both neighborhood-level and edge-level dropout are adopted in a parallel way to allow more comprehensive information distillation. We conduct an in-depth experimental evaluation on three real-world datasets, comparing our proposed HKRec with state-of-the-art baseline models to demonstrate its effectiveness and superiority. Respectively, Recall@20 and NDCG@20 improved by 2.2% to 24.95% and 3.38% to 22.32% in the Last-FM dataset, by 7.0% to 23.82% and 5.7% to 39.66% in the MIND dataset, and by 1.76% to 34.73% and 1.62% to 35.13% in the Alibaba-iFashion dataset. Full article

The four-switch buck-boost (FSBB) converter usually adopts a pseudo-continuous conduction mode (PCCM) soft switching (ZVS) control strategy, but there is a problem with the low efficiency of FSBB converters under light loads. Firstly, the constraints that the control variables of the FSBB converter need to satisfy are analyzed, and it is pointed out that the fixed frequency constraint is not necessary. Then, the switching frequency is used to control the degree of freedom, and the quantitative relationship between the FSBB converter loss and the switching frequency is obtained. Finally, for different input voltages and loads, the switching frequency corresponding to the minimum power loss is calculated offline. By optimizing the switching frequency, the light-load efficiency of the FSBB converter is improved. A prototype with an input voltage range of 210 V–330 V, an output voltage of 270 V, and an output power of 3 kW was developed. The loss was reduced by 15% at 20% load, and the peak efficiency of the converter reached 99.23%. The experimental results verified the effectiveness of the proposed control strategy. Full article

We study numerical methods and algorithms for time-dependent fractional-in-space diffusion problems. The considered anomalous diffusion is modelled by the fractional Laplacian ${(-\Delta )}^{\alpha }$, $0<\alpha <1$, following the integral definition. Fractional diffusion is non-local, and the finite element method (FEM) discretization in space leads to a dense stiffness matrix. It is well known that numerically solving such non-local boundary value problems is expensive. Difficulties increase significantly when the problem is time-dependent. The aim of the article is to develop computationally efficient methods and algorithms. There are two main features of our approach. Hierarchical semi-separable (HSS) compression is applied for an approximate solution of the arising linear systems. For time discretization, we use an adaptive forward–backward Euler scheme. The properties of the composite algorithm thus obtained are investigated. In particular, the block representation of HSS compression allowed us to upgrade the HSS solver to efficiently handle varying diagonally perturbed transition matrices corresponding to changing time steps. The contribution of the paper is threefold. The methods are completely constructive, which allows for a clearly structured description of the algorithms. A theoretical estimate of the computational complexity is presented. It shows the advantages of the adaptive time stepping in combination with the HSS solver. Theoretical results are supported by representative numerical experiments. Both sequential and parallel scalability and efficiency are analyzed. The presented results provide convincing proof of the concept of the proposed methods and algorithms. Full article

Higher lighting intensity promotes workers’ productivity but few studies focus on the problems caused by lower lighting intensities at tunnel construction sites without natural light. The purpose of this study is to explore the relationship between light intensity and workers’ sleep quality, alertness, vitality, and work productivity through a theoretical structural equation model based on the literature review. Data were collected through a questionnaire survey, and 5792 valid responses were adopted for the analysis. First, the results showed that greater lighting intensity promoted workers’ productivity directly and indirectly through three mediators: sleep quality, alertness, and vitality. Then, the whole sample was classified into four groups: high intensity/high comfort, moderate intensity/moderate comfort, moderate intensity/low comfort, and low intensity/low comfort. The clustered results showed that the lighting conditions of tunnel construction sites were generally poor and that lighting comfort promoted workers’ productivity to some extent. Besides, the influence of lighting intensity on productivity declined with improved lighting conditions while the impact of lighting intensity on workers’ physiological and psychological status showed differing trends as lighting conditions varied. However, the relationships between workers’ physiological and psychological status and productivity remained stable regardless of the lighting conditions. The findings could provide a reference for developing corresponding measures to promote workers’ productivity. Full article

Modeling of various phenomena in engineering work is always a kind of simplification of real processes, aiming at a model where a certain level of mathematical theory and computational procedures is sufficient. If the complexity of the required theory corresponds to the general mathematical competence of engineers, then technical problems can be treated separately in engineering (or physical) models without regard to the mathematical background. However, in some advanced engineering fields, the harmonized development of engineering and mathematical models and toolboxes is necessary to find efficient solutions. For example, modeling variable structure systems in ideal sliding mode requires a mathematical toolbox that goes far beyond general engineering competence through the theory of discontinuous right-hand-side differential equations. Although sliding mode control is popular in practice and the concept of sliding mode allows a significant reduction of model complexity, its exact mathematical description is rarely encountered. The problem of friction compensation of a micro-telemanipulator using sliding mode control demonstrates a harmonized application of the mathematical and engineering approaches. Based on Filippov’s theory, the ideal sliding mode can be discussed. Although an ideal system cannot be implemented in reality, the real systems can be kept close enough to it; therefore, the discussion of the solution of the ideal model is important for practical applications. Although several elements of the topic are available in the literature, in this paper a unique complex approach is given for users of sliding mode control with experimental considerations, different engineering models, and codes. The paper concludes that sliding mode control is a case where engineering and mathematical modeling are inseparable and requires the competence of both fields. Full article

Background: With the increase in the elderly population, institution-based care has become another option for elderly people. In Changhua, Taiwan, the number of long-term institutions has doubled in the past decade, and more families are choosing to send their elders to institutions for care. However, there is stress induced by having to care for these elders when they come back to their family members when hospitalized. Therefore, this study aimed to understand the stress and coping behaviors of family members in regard to hospitalized long-term care facility residents and identify relevant factors that affect and predict the stress and coping behaviors exhibited by these family members. Method: In this study, a quantitative and cross-sectional survey was conducted using the convenience-sampling method; family members of long-term care facility residents hospitalized in a regional hospital in central Taiwan were selected as the research participants and a total of 162 family members were admitted. The data were collected in the form of questionnaires including basic information and data on the stress and coping behaviors of the family members. The data were collected and coded by using SPSS 22.0 to perform descriptive and inferential statistical analysis. Results: The standard average score of total stress for family members was 57.03 points, which corresponds to a moderate level. The four perceptions of stress by family members were, in order, physiological, life, psychological, and economic. Furthermore, family income, work status, and the relationship between residents of the family members and physiological, psychological, and economic factors had predictive power for their problem-oriented coping behaviors, with an explanatory power of 59.6%. Life aspects, gender, marital status, and the number of hospitalizations in half a year had significant predictive power for the family members’ emotion-oriented coping behaviors, with an explanatory power of 19.0%. Conclusions: The family members had high levels of stress, especially physical stress, and the total scores of stress perception were higher for those who were younger than 39 years old and had no rotating family members. Additionally, the coping behavior of the main caregiver was mainly problem-oriented. The results of this study may serve as a reference that can help nursing staff in clinical or long-term care facilities to provide or develop effective and individualized services for family members of facility residents. Full article

This article aims to present the mechanisms regulating the waste management system of one of the European countries that affect the cement industry. This publication analyses the possibility of using selected fractions of municipal and industrial waste as alternative fuels, including an analysis of ecological costs and benefits. The methodology includes the analysis of production data and the calculation of savings resulting from the use of alternative fuels. On this basis, ecological aspects were also indicated that should be taken into account when analyzing the profitability of the investment. Production data from an example Polish cement plant were used to analyze the research problem. Based on the guidelines of environmental standards and technical specifications, the parameters that PASr alternative fuels should meet were calculated in the company laboratory. This fuel type was then calculated in terms of emission intensity and production efficiency. The research results obtained in this paper study emphasize that the change in cement clinker production technology toward the use of waste raw materials and secondary fuels does not lead to an increase in heavy metal emissions to the extent that would justify qualifying cement as a material requiring systematic control of its harmful impacts on humans and the natural environment. The conclusions show that the use of alternative fuels reduces CO₂ emissions and production costs, without negatively affecting the efficiency and production volume. The average energy requirement for the production of 1 ton of cement is approximately 3.3 GJ, which corresponds to 120 kg of coal with a calorific value of 27.5 MJ per kg. Energy costs account for 30–40% of the total cement production costs. Replacing alternative fuels with fossil fuels will help reduce energy costs, providing a competitive advantage for cement plants that use it as an energy source. The presented considerations can provide an answer to all interested parties, including representatives of the executive and legislative authorities, on what path the sector should follow to fit into the idea of sustainable building materials and the circular economy. Full article

The commonly used baseline-free Lamb wave damage identification methods often require a large amount of sensor data to eliminate the dependence on baseline signals. To improve the efficiency of damage localization, this paper proposes a new Lamb wave damage location method, namely the probabilistic exchanging-element time-reversal method (PEX-TRM), which is based on the exchanging-element time-reversal method (EX-TRM) and the probabilistic damage identification method. In this method, the influence of the damage wave packet migration on the correlation coefficient between the reconstructed signals of each sensing path and the initial excitation signal is analyzed, and the structure is divided into multiple regional units corresponding to the damage to locate damage. In addition, the influence of the number of sensing paths on the location accuracy is also analyzed. A method of damage probability imaging based on structural symmetry is proposed to enhance location accuracy in the case of sparse sensing paths. The experimental and simulation results verify that the method can achieve damage location with fewer excitation times. Moreover, this method can avoid the problem that the damage wave packet is difficult to extract, improve the efficiency of damage location, and promote the engineering application of the Lamb wave damage location method. Full article

We study a two-dimensional system of interacting electrons confined in equidistant planar circular rings. The electrons are considered spinless and each of them is localized in one ring. While confined to such ring orbits, each electron interacts with the remaining ones by means of a standard Coulomb interaction potential. The classical version of this two-dimensional quantum model can be viewed as representing a system of electrons orbiting planar equidistant concentric rings where the kinetic energy may be discarded when one is searching for the lowest possible energy. Within this framework, the lowest possible energy of the system is the one that minimizes the total Coulomb interaction energy. This is the equilibrium energy that is numerically determined with high accuracy by using the simulated annealing method. This process allows us to obtain both the equilibrium energy and position configuration for different system sizes. The adopted semi-classical approach allows us to provide reliable approximations for the quantum ground state energy of the corresponding quantum system. The model considered in this work represents an interesting problem for studies of low-dimensional systems, with echoes that resonate with developments in nanoscience and nanomaterials. Full article

LSTM (long short-term memory) networks have been proven effective in processing stock data. However, the stability of LSTM is poor, it is greatly affected by data fluctuations, and it is weak in capturing long-term dependencies in sequential data. BiLSTM (bidirectional LSTM) has alleviated this issue to some extent; however, due to the inefficiency of information transmission within the LSTM units themselves, the generalization performance and accuracy of BiLSTM is still not very satisfactory. To address this problem, this paper improves LSTM units on the basis of traditional BiLSTM and proposes a He-BiLSTM (heterogeneous bidirectional LSTM) with a corresponding backpropagation algorithm. The parameters in He-BiLSTM are updated using the Adam gradient descent method. Experimental results show that compared to BiLSTM, He-BiLSTM has further improved in terms of accuracy, robustness, and generalization performance. Full article

For highly reliable software systems, it is expensive, time consuming, or even infeasible to perform reliability testing via a conventional software reliability demonstration testing (SRDT) plan. Moreover, in the traditional SRDT approach, the various characteristics of the software system or test sets are not considered when making the testing schemes. Some studies have focused on the effect of software testability on SRDT, but only limited situations were discussed, and many theoretical and practical problems have been left unresolved. In this paper, an extended study on the quantitative relation between test effectiveness (TE) and test effort for SRDT is proposed. Theoretical derivation is put forward by performing statistical analysis for the test suite according to TE. The combinations of all the cases of zero-failure and revealed nonzero failure, as well as discrete-type software and continuous-type software, are studied with the corresponding failure probability models constructed. That is, zero-failure and nonzero failure, as well as discrete-type software and continuous-type software, respectively, constitute the symmetry and asymmetry of SRDT. Finally, we illustrated all the models and performed applications on the Siemens program suite. The experimental results show that within the same limitation of requirements and confidence levels, this approach can effectively reduce the number of test cases and the test duration, i.e., accelerate the test process and improve the efficiency of the SRDT. Full article

In this work, we analyze a spherically symmetric 3D flow of a micropolar, viscous, polytropic, and heat-conducting real gas. In particular, we take as a domain the subset of $R^3$ bounded by two concentric spheres that present solid thermoinsulated walls. Also, here, we consider the generalized equation of state for the pressure in the sense that the pressure depends, as a power function, on the mass density. The model is based on the conservation laws for mass, momentum, momentum moment, and energy, as well as the equation of state for a real gas, and it is derived first in the Eulerian and then in the Lagrangian description. Through the application of the Faedo–Galerkin method, a numerical solution to a corresponding problem is obtained, and numerical simulations are performed to demonstrate the behavior of the solutions under various parameters and initial conditions in order to validate the method. The results of the simulations are discussed in detail. Full article