Design and Simulation of a Garlic Seed Metering Mechanism

According to the agronomic requirements of garlic sowing, the garlic morphology is studied and a garlic seed metering mechanism with excellent seeding performance is designed. Based on this design, a new garlic seeding machine with an adjustable-size seeding device is developed to realize efficient single-seed metering and seeding of different varieties of garlic. Further, the design scheme of the garlic seeder prototype is established, with the key components of the garlic seeding being designed on the basis of the garlic seeding mechanism. To achieve garlic single-seed metering for different varieties of garlic, the optimal adjustment size of the garlic seed metering device is determined through discrete element simulation analysis. A field experiment confirms the effectiveness of applying the proposed garlic planter to field sowing in terms of the metrics of missing seed and multiple seed rates. The results of the discrete element simulation test reveal that an adjustment size of 40 mm yields the best single-seed metering performance. At an operating speed of 15–35 rpm, the metering device can achieve more than an 80% qualification rate of single-seed metering, with a unit speed of 0.628–1.465 m/s. Thus, the developed garlic seeding device meets the requirements of precision sowing in China and can effectively realize the mechanized planting of garlic.

Optimal Adjustment of Evolutionary Algorithm-Based Fuzzy Controller for Driving Electric Motor with Computer Interface

This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.<div>Note : This article has been accepted for publication in a future issue of ELECTRICA journal, it is now in the early view. </div><div>Citation information: </div><div>M. Bulut, "Optimal Adjustment of Evolutionary Algorithm-based Fuzzy Controller for Driving Electric Motor with Computer Interface", Electrica, August 5, 2021. DOI: 10.5152/electrica.2021.21033.</div>

Analyzing the Solution of Chemotaxis Equations with Logistic Source Term

When the parameters have the characteristics of sensitivity and specificity, while the traditional analysis method is the analysis of equations, under the influence of the characteristics of parameters, because the ability to consider the overall existence and limitations of the equation is weak, this leads to the deviation of the analysis results beyond the allowable range. With the chemotactic equations with logistic source terms, a new analysis method is proposed, on the basis of setting the optimal adjustment parameters of logistic source term, the method evaluates the well-posed behavior of the solution of the chemotactic equation system with logistic source term by quantitative analysis of the global existence and limitations of the solution. The experimental results show that the proposed analysis method, after the analysis of the overall existence and limitations of the equation, has smaller deviation in the results of the appropriate qualitative evaluation and meets the analysis requirements of the solution problem of the chemotaxis equations. It can be seen that the analysis method is more practical.

ADJUSTMENT OF A PID REGULATOR USING TRANSIENT FUNCTION OF THE OPEN CONTROL LOOP

The problem of optimal adjustment of a PID regulator, which is basic algorithm for automatic control systems for thermal plants, remains relevant. A simple and practical method of adjustment the PID regulator, using the transient function of the open control clop in the time domain is offered, convenient for practical use. The optimal graph of the transient function of the open control loop should be a broken straight line with delay. By varying time constants of the integration and differentiation channels of the PID regulator, the graph of the transient function of the open control loop should be straightened, that is converted to a straight line with delay. Variating the proportionality factor of the regulator, the growth rate (slope of the graph) of the transient function should be made 0.52, relative to its delay. Adjusting the PID regulator according to the proposed method guarantees the minimal possible regulation time. The proposed method for adjusting the parameters of a PID regulator is recommended to be used both for the computer simulation of the regulation dynamics and for operating systems of automatic control.

Dynamic Markov Model: Password Guessing Using Probability Adjustment Method

In password guessing, the Markov model is still widely used due to its simple structure and fast inference speed. However, the Markov model based on random sampling to generate passwords has the problem of a high repetition rate, which leads to a low cover rate. The model based on enumeration has a lower cover rate for high-probability passwords, and it is a deterministic algorithm that always generates the same passwords in the same order, making it vulnerable to attack. We design a dynamic distribution mechanism based on the random sampling method. This mechanism enables the probability distribution of passwords to be dynamically adjusted and tend toward uniform distribution strictly during the generation process. We apply the dynamic distribution mechanism to the Markov model and propose a dynamic Markov model. Through comparative experiments on the RockYou dataset, we set the optimal adjustment degree α. Compared with the Markov model without the dynamic distribution mechanism, the dynamic Markov model reduced the repetition rate from 75.88% to 66.50% and increased the cover rate from 37.65% to 43.49%. In addition, the dynamic Markov model had the highest cover rate for high-probability passwords. Finally, the model avoided the lack of a deterministic algorithm, and when it was run five times, it reached almost the same cover rate as OMEN.

A Fast Directional Overcurrent Relay Coordination Method for Smart Grid Protection

Modern power systems are dynamic and complex. Likewise, smart grids bring opportunities for the development of protection relays, such as the ability to communicate remotely. Based on these opportunities, this paper proposes a method of coordinating directional overcurrent relays capable of quickly obtaining the optimal adjustment of the relays with each topological change in the network. The proposed methodology is applied in different cases to a test system, demonstrating its effectiveness and potential.

Collaboration Strategy Based on Conflict Resolution for Flatness Actuator Group

During the flatness control process, there are frequently some uncoordinated regulating behaviors in the flatness actuator group. This has a bad influence on the flatness control accuracy and the flatness control efficiency. Therefore, a collaboration strategy based on conflict resolution for the flatness actuator group has been proposed in this paper. First of all, the feature of flatness measurement value is extracted through establishing the actual flatness condition discriminating factor. After that, the coordination cooperation that is appropriate to the actual flatness condition is developed for the flatness actuator group. Finally, the optimal adjustment of the actuator population is solved by the coordinated algorithm of Topkis-Veinott and genetic algorithm collaborative optimization. The collaboration strategy proposed in this paper has been successfully applied to a flatness control system of a 1450 mm five-stand cold rolling mill.

Association of Depression with Uncontrolled Hypertension in Primary Care Setting: A Cross-Sectional Study in Less-Developed Northwest China

Background. Hypertensive patients commonly experience comorbid depression, which is closely associated with adverse health outcomes. This study aimed to examine the association between depression and uncontrolled hypertension in primary care setting of Northwest China. Methods. We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years among primary care setting in Xinjiang, Northwest China, between April and October 2019. Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. We related depression to uncontrolled hypertension, using multiple logistic regression, adjusting for minimally sufficient adjustment set of variables retrieved from a literature-based directed acyclic graphs (DAGs) and optimal adjustment set of variables derived from the least absolute shrinkage and selection operator (LASSO) regression. Results. A total of 1,653 (89.1%) patients had uncontrolled hypertension. The prevalence of depression was 14.5% and 7.4% among patients with uncontrolled and controlled hypertension. Depression was associated with 1.12-fold increased odds of uncontrolled hypertension [odds ratio (OR) 2.12, 95% confidence interval (CI): 1.23–3.65]. The association remained significant even after adjusting for the minimal sufficient adjustment sets and the optimal adjustment set of variables. Conclusion. Depression is significantly associated with uncontrolled hypertension in primary care setting of northwest China. The integrated management of depression and hypertension in the setting might be warranted.