Optimal Frequency Research Articles

Bridging the gap between crop breeding and GeoAI: Soybean yield prediction from multispectral UAV images with transfer learning

Despite significant progress has been made towards crop yield prediction with remote sensing, there exist knowledge gaps on (1) the impacts of temporal resolution of imaging frequencies on yield prediction, (2) transferability of the models among different genotypes and test sites, and (3) translation of these research developments to crop breeding that benefit farmers. Existing research predominantly provides an on-site perspective, frequently missing the complexities of real-world applications. The objectives of this paper are to investigate the transferability and generalization capabilities of yield prediction models for crop breeding across test sites located in North and South Americas. Toward that goal, we tested different machine learning techniques including Random Forest Regressor (RF), Gradient Boosting Regression (GB), and Deep Neural Networks (DNN) for soybean yield prediction with experiments conducted in different climate and growth conditions. A novel transfer learning approach was proposed for genotype selection and categorizing soybean yield for screening high-yield varieties. Furthermore, we studied the effect of temporal resolution on yield prediction, focusing on the critical development stages and optimal aerial survey frequencies for precise yield prediction using large 31,404 sample data. Results demonstrated that the combined dataset of Argentina and United States representing different climate regimes provided the highest performance with an R2 of 0.76 using RF and GB algorithms. The classification approach was proven to be most useful for crop breeding as demonstrated by accurately identifying the high-yielding genotypes. Increasing temporal sampling of key phenological stages significantly improved yield prediction. Although transfer learning yielded promising outcomes across trials within Argentina the efficacy of transferring models from Argentina to the United States was limited, attributed to significant seasonal and climate variations. This study pioneered the use of transfer learning for model adaptability in real-world breeding scenarios, training and transferring models within the South and North Americas, providing actionable insights and strategies for the breeding community, aiming to facilitate improved decision-making for agricultural productivity.

Multi-segment droop control and optimal parameter setting strategy of wind turbine for frequency regulation

Traditionally, virtual inertia is used as the control strategy for wind turbines when participating in frequency regulation. However, it has inherent defects in measurement error amplification due to the frequency differential. Also, when control delay of wind turbines is taken into consideration, virtual inertia is essentially a fast power response, just the same as droop control. Hence, considering the adaptability of droop control, it is valuable to explore a novel droop control method without virtual inertia, as the frequency response model of wind turbines. For this reason, a multi-segment droop control strategy is proposed to provide a reliable frequency regulation model for wind turbines that can be broadly applied to other inverter-based power sources. Firstly, based on the extended system frequency response model, a differential equation including piecewise time-varying coefficients is established, and the analytical expression of the frequency response is obtained using the impulse function balancing principle and the integration by parts algorithm. Subsequently, based on analytical expression, the performance of the presented strategy is theoretically analyzed via comparison with virtual inertia control, and the conclusion that the presented multi-segment droop control has better frequency regulation performance can be got. Furthermore, to achieve optimal frequency regulation performance, a Lagrangian function is established to determine the optimal parameters of the proposed control strategy. Finally, the performance of the proposed strategy was verified in a two-area system model constructed on MATLAB/Simulink. Results show that the proposed multi-segment droop control has better frequency regulation performance.

Design of an ultra wideband THz reflectarray antenna based on orbital angular momentum

A Reflectarray antenna (RA) that can generate orbital angular momentum vortex waves in the THz band was proposed. First of all, a reflective phase-shifting element composed of a notched double-shaped ring and a single Matal structure was designed to form a radiation patch. The reflective phase-shifting element has the advantages of good linearity, high smoothness, and a large phase shift range, which is suitable for the subsequent production of reflective array antennas. Then, the phase distribution of the reflected wave of the OAM vortex wave carrying mode l=+1、+2、+3、+4 is given, and the size of each element is determined based on the reflected phase of each element. Using the proposed element, an OAM reflectarray antenna operating within the waveguide standard WR-5 (120GHz–220GHz) is designed. The optimal frequency band for antenna operation in mode l=+1 is 150GHz–190 GHz, and the maximum gain of the reflector array antenna is 19.4 dBi, and the minimum divergence angle of the antenna array is 5.2°, which has good directivity and beam radiation ability. The spiral structure of the OAM beam space generated by the RA in this paper is clearly visible, proving that the implementation of OAM vortex waves in the THz frequency band is feasible. This design also provides a new method for generating OAM vortex waves in wireless and microwave wireless communications. The proposed RA is suitable for 6G wireless communication systems.

Virtual Reality Relaxation for Stress in Young Adults: A Remotely Delivered Pilot Study in Participants’ Homes

AbstractHigh stress levels experienced by young adults were exacerbated by COVID-19 and traditional stress management techniques can be challenging. Virtual reality (VR) relaxation appears promising and is accessible remotely; however, research on young adults is limited, especially in naturalistic settings. This remotely delivered and controlled mixed-methods study investigated feasibility and acceptability of VR relaxation for young adults (N = 23, mean age = 22.96) at home during the pandemic. VR participants (N = 11) were asked to complete daily VR relaxation sessions (scenes of virtual beaches, mountains, the sea, and more) for a 14-day intervention period, alongside visual analogue scales (VAS) of psychological well-being pre- and post-VR sessions. Post-intervention, VR participants completed semi-structured interviews. Control participants (N = 12) received no intervention. Both groups completed outcome measures of psychological well-being pre- and post-intervention periods to evaluate feasibility of remote data collection. VAS results indicated acceptability of daily VR, with significant short-term increases in relaxation, happiness, and connectedness to nature, and decreases in stress, anxiety, and sadness within VR participants. VR usage and 100% completion of outcome measures indicated feasibility of VR relaxation and remote data collection. Qualitative findings suggest participants found the VR relaxing, but interest diminished over time and technical issues hindered user experience. This suggests a more informal, less prescriptive frequency of VR use may be more appealing for young adults, although adherence may relate to technical issues. Greater interactivity and remote technical assistance within VR could increase engagement. Future research should investigate optimal frequency of use, longer-term impact, and technical issues with a larger sample.

Increasing the Energy Efficiency of Traction Electric Drives of Direct Current

Purpose. The work is aimed at improving the energy efficiency of direct current traction electric drives of electric transport by introducing transistor pulse width converters (PWC) with an optimal switching frequency to minimize total electrical losses in the electric drive. The electrical losses of traction electric drives consist of electrical losses in the armature winding and in the PWC transistors. Methodology. To study the dependence on the switching frequency of transistors, the electrical losses in the armature winding and PWC transistors are divided into two parts: static losses from the direct current component of the current and dynamic losses, i.e., losses in the armature winding from harmonic current components and losses in the transistors from transient switching currents. Since the dynamic electrical losses in transistors increase with increasing frequency and decrease in the armature winding, it is necessary to find the optimal PWC co-mutation frequency at which the total dynamic losses in the traction electric drive will be minimal. The goal of increasing energy efficiency in a traction electric drive is achieved by determining the dependence of dynamic electrical losses in the armature winding on the switching frequency of the PWC and computer modeling of the transistor electric drive. Findings. It is found that the relative dynamic electrical losses in the armature winding in the case of polyharmonic power supply are equal to the square of the armature current ripple coefficient. An algorithm for determining the optimal switching frequency of the PWC is developed: 1) the dependence of dynamic electrical losses on the switching frequency of transistors is determined experimentally on computer models of the motor and PWC; 2) the graph of the dependence of total dynamic electrical losses of the transistor electric drive on the time-tothe point of minimum losses, which corresponds to the optimal frequency value, is determined. Originality. For the first time, the authors obtained an analytical expression for the relative dynamic electrical losses in the armature windings, which are equal to the square of the armature current ripple factor. Practical value. Establishing the optimal switching frequency of the PWC according to the developed methodology reduces electrical losses in traction electric drives, i.e., increases their energy efficiency.

Effect of Ventilator Settings on Mechanical Power During Simulated Mechanical Ventilation of Patients With ARDS.

In recent years, mechanical power (MP) has emerged as an important concept that can significantly impact outcomes from mechanical ventilation. Several individual components of ventilatory support such as tidal volume (VT), breathing frequency, and PEEP have been shown to contribute to the extent of MP delivered from a mechanical ventilator to patients in respiratory distress/failure. The aim of this study was to identify which common individual setting of mechanical ventilation is more efficient in maintaining safe and protective levels of MP using different modes of ventilation in simulated subjects with ARDS. We used an interactive mathematical model of ventilator output during volume control ventilation (VCV) with either constant inspiratory flow (VCV-CF) or descending ramp inspiratory flow, as well as pressure control ventilation (PCV). MP values were determined for simulated subjects with mild, moderate, and severe ARDS; and whenever MP > 17 J/min, VT, breathing frequency, or PEEP was manipulated independently to bring back MP to ≤ 17 J/min. Finally, the optimum VT-breathing frequency combinations for MP = 17 J/min were determined with all 3 modes of ventilation. VCV-CF always resulted in the lowest MPs while PCV resulted in highest MPs. Reductions in VT were the most efficient for maintaining safer and protective MP. At targeted MPs of 17 J/min and maximized minute ventilation, the optimum VT-breathing frequency combinations were 250-350 mL for VT and 32-35 breaths/min for breathing frequency in mild ARDS, 200-350 mL for VT and 34-40 breaths/min for breathing frequency in moderate ARDS, and 200-300 mL for VT and 37-45 breaths/min for breathing frequency for severe ARDS. VCV-CF resulted in the lowest MP. VT was the most efficient for maintaining safe and protective MP in a mathematical simulation of subjects with ARDS. In the context of maintaining low and safe MPs, ventilatory strategies with lower-than-normal VT and higher-than-normal breathing frequency will need to be implemented in patients with ARDS.

Ultrasonic resonance evaluation method for deep interfacial debonding defects of multilayer adhesive bonded materials

Abstract Multilayer adhesive bonded structures/materials (MABS) are widely used as structural components, especially in the field of aerospace. However, for MABS workpieces, the facts that the weak echo of the deep interfacial debonding defects (DB) caused by the large acoustic attenuation coefficient of each layer and this echo, which generally aliases with the excitation wave and the backwall echo of the surface layer, pose a great challenge for the conventional longitudinal wave ultrasonic nondestructive testing methods. In this work, an ultrasonic resonance evaluation method for deep interfacial DBs of MABS is proposed based on the ultrasonic resonance theory and the aliasing effect of ultrasonic waves in MABS. Theoretical and simulation analysis show that the optimal inspection frequency for II-interfacial DBs is 500 kHz when the shell thickness is 1.5 mm and the ethylene propylene diene monomer (EPDM) thickness is 1.5 mm, and the optimal inspection frequency is 250 kHz when the shell thickness is 1.5 or 2.0 mm and the EPDM thickness is 2.0 mm. Verification experiments show that the presence of a DB in the II-interface causes a resonance effect, and in the same inspection configuration, the larger the defect size, the more pronounced this effect is. This resonance effect manifests itself as an increase in the amplitude and an increase in the vibration time of the A-scan signal as well as a pronounced change in the frequency of the received ultrasonic wave. In addition, the increase in the excitation voltage further highlights the ultrasonic resonance effect. Four imaging methods – the integrations of the signal and the signal envelope curve, the maximum amplitude of the fast Fourier transform (FFT) of the signal, and the signal energy – were used for C-scan imaging of ultrasonic resonance evaluation of MABS’s deep interfacial DBs and all these methods can clearly show the sizes and locations of the artificial defects and internal natural defect. The normalized C-scan imaging method proposed in this study can further highlight the weak changes in the signals in the C-scan image. The research results of this study have laid a solid theoretical and practical foundation for the ultrasonic resonance evaluation of MABS.

On the relationship between free public transport, stop spacing, and optimal frequencies

Recent years have witnessed a reignition of the debate about free public transport, especially after a wider implementation due to the pandemic. However, most implementations have consisted of eliminating the fare without further structural adjustments, and one of the main reported concerns is that they seem to primarily attract commuters from active modes rather than car drivers. In this paper, we develop an analytical model to investigate how the design of a representative public transport line, situated in a corridor where it competes with both walking and cars, should be adjusted in response to fare reductions. We first conduct a detailed analysis of the effect of frequency and spacing on mode choice, showing that while increased frequencies attract both walkers and drivers, an increased spacing tends to attract long-distance commuters (often drivers) and discourage short-distance ones (which are more likely to walk). Hence, spacing can play a crucial role in inducing a desired mode choice.Afterwards, we study the optimal response of public transport design under two possible objectives. If the aim is to minimise users’ plus operator’s costs in public transport, a decrease in the fare should be joined by an increased frequency and, potentially, a reduced spacing. If the objective is to induce a more sustainable mode split, the measures are the opposite: increase spacing and reduce frequencies. These divergent findings show that it is crucial to have a clear goal when reducing the fare, as no singular policy can achieve all of the objectives. We remark that an increased spacing and reduced frequency reduce the financial burden of the system, although it is most likely not enough to compensate for the loss of revenue when fares go free.

Renewable energy resource integrated multilevel inverter using evolutionary algorithms

In this paper, with the development of an intelligent power system idea, sustainable energy sources were increasingly deployed, including transmission and distribution systems networks. As a result, optimal use of cascaded H-bridge inverter topologies (MLIs) and power distribution operations is critical for long-term power generation. Traditionally, selective harmonics reduction models must be performed to achieve the optimal switching frequency of multilevel inverters. This research aims to determine the switching frequency for wind-incorporated multilevel inverters to reduce overall harmonic components used in grid applications. This research adds towards the best possible solution by employing multiple newly established adaptive optimization techniques: MNSGA-II and salp swarm. The well-known genetic algorithm and particle swarm optimization are used for the wind-tied multilevel inverters optimization issue. Seven-level, eleven-level, and fifteen-level MLIs were employed to reduce overall harmonic distortion. The reliability and convergence rate of simulated data with various modulation indices for seven-, eleven-, and fifteen-level MLIs are obtained and compared. Models are developed based on MATLAB Simulink and are used to validate quantitative measurements.

Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes

Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from local instability in the sense that the frequency of states visited in a bounded time horizon along a run differs significantly from the limit frequency. In this work, we propose an efficient algorithmic solution to this problem.

Ensefgram: An optimal demodulation band selection method for the early fault diagnosis of high-speed train bearings

Early fault diagnosis of high-speed train bearings under road spectrum shocks is challenging. As a conventional narrowband demodulation method, the Fast Kurtogram (FK) class of algorithms have some drawbacks: the fixed-band segmentation strategy makes it difficult for the method to find the optimal demodulation frequency band (ODFB); other major limitations are the poor robustness of the statistical index of the blind algorithm and the poor adaptiveness of the target algorithm given the need to the know the bearing operating state in advance. To address these issues, this paper proposes Ensefgram, an early fault detection method for high-speed train bearings with the acoustic emission signal as an example. First, a filter bank is designed by combining the spectral trend with the median dichotomy strategy, which adaptively segments the frequency band and retains the integrity of the sub-band fault components to the maximum extent. In addition, a novel statistical index, termed the maximum weighted spectral energy frequency factor, is proposed, and it is combined with the envelope spectrum negentropy (ES-negentropy) to form a composite index ENSEF, which can select the ODFB blindly. Finally, the proposed method was validated by simulation and applying test signals close to the real working conditions of a high-speed train. Compared with FK, Infogram, and other methods, Ensefgram provides more accurate detection results for the early fault diagnosis of bearings.

Effect of flow pulsation on heat transfer performance of biomimetic bark microchannel heat sink

Pumping coolant or using pulse flow through microchannels with novel structures on microelectronic devices is suitable for high heat flux dissipation and sensor development. This study proposes a novel microchannel designed as a series of biomimetic bark channel networks. Simulation and experimental testing of temperature distribution and heat transfer performance are conducted under different working conditions, including various fluid parameters. The results show that combining biomimetic bar microchannel and pulsation flow can improve heat transfer performance. The effect of pulsating flow frequency on the temperature is only evident outside the range of 10 mm from the inlet. Compared with non-slip boundaries, the boundary slip of pulsating flow slightly enhances heat transfer. Pulsating flow has an optimal frequency, minimizing thermal resistance for different inlet temperatures.

A Study on the Effectiveness of Telemarketing in the Banking Industry

This study examines the effectiveness of telemarketing in the banking industry, with a focus on identifying the optimal timing and frequency of telemarketing calls for maximizing sales conversion, measuring customer satisfaction with telemarketing calls, determining the impact of telemarketing on customer retention, and identifying factors that influence the success of telemarketing campaigns. To accomplish these objectives, a mixed-methods approach will be used, including surveys, interviews, and data analysis. The study aims to provide insights into how banks can develop more effective telemarketing strategies that generate more revenue, improve customer satisfaction, and increase customer retention. The findings of this study can be used by banks to optimize their telemarketing efforts and enhance their customer relationships.

A Study on the Effectiveness of Telemarketing in the Banking Industry

This study examines the effectiveness of telemarketing in the banking industry, with a focus on identifying the optimal timing and frequency of telemarketing calls for maximizing sales conversion, measuring customer satisfaction with telemarketing calls, determining the impact of telemarketing on customer retention, and identifying factors that influence the success of telemarketing campaigns. To accomplish these objectives, a mixed-methods approach will be used, including surveys, interviews, and data analysis. The study aims to provide insights into how banks can develop more effective telemarketing strategies that generate more revenue, improve customer satisfaction, and increase customer retention. The findings of this study can be used by banks to optimize their telemarketing efforts and enhance their customer relationships.

Generation of entangled waveguided photon pairs by free electrons.

Entangled photons are a key resource in quantum technologies. While intense laser light propagating in nonlinear crystals is conventionally used to generate entangled photons, such schemes have low efficiency due to the weak nonlinear response of known materials and losses associated with in/out photon coupling. Here, we show how to generate entangled polariton pairs directly within optical waveguides using free electrons. The measured energy loss of undeflected electrons heralds the production of counter-propagating polariton pairs entangled in energy and emission direction. For illustration, we study the excitation of plasmon polaritons in metal strip waveguides that strongly enhance light-matter interactions, rendering two-plasmon generation dominant over single-plasmon excitation. We demonstrate that electron energy losses detected within optimal frequency ranges can reliably signal the generation of plasmon pairs entangled in energy and momentum. Our proposed scheme is directly applicable to other types of optical waveguides for in situ generation of entangled photon pairs.

Vibration response characteristics of Jujube trees based on finite element method and structure-from-motion

It is an indispensable step to choose optimal vibration parameters in jujube fruits vibration harvesting. Excessive vibration frequency will cause jujube tree damage, otherwise, the separation of fruit and fruit stalk cannot be achieved, resulting in harvesting failure. In our work, finite element method and vibration tests are applied to find optimal vibration parameters. To improve the accuracy of finite element method, a low-cost 3D reconstruction method is proposed to build jujube tree model. Experimental result showed that the phenotypic information of the reconstructed jujube tree and the real jujube tree have a high similarity, and their determination coefficient R2 reach to 0.984. Moreover, the natural frequencies of jujube tree are analyzed by modal analysis, transient analysis is applied to analyze vibration transfer characteristics. The simulation and experimental results show that the optimal vibration frequency range of jujube tree is 25∼30 Hz, the optimal vibration excitation location is on the main trunk and as high as possible close to the secondary branches, which can obtain maximum vibration response for optimum harvesting efficiency. The average determination coefficient is 0.66 between test and simulation results at different frequencies. This study can provide references for accurate 3D modeling of jujube trees, selection of appropriate vibration parameter range and the development of jujube harvesting machinery.

Improvement of contrast ratio between cavitation bubbles and tissue by frequency filtering in triplet pulse ultrasound imaging

Bubble-enhanced high-intensity focused ultrasound treatment requires selective imaging of cavitation bubbles to ensure their localization to the target tissue. Previous studies have proposed the ultrasound imaging of cavitation bubbles with a filtering method, which makes bubble extraction by a triplet pulse sequence more selective. The envelope component as well as harmonic components are generated during the nonlinear propagation of an ultrasonic imaging pulse, but the triplet pulse sequence can significantly reduce only the harmonic components, and its selectivity is degraded by the residual envelope component. In this study, the effects of nonlinear propagation at various intensities of imaging pulse and the frequency filtering to obtain better selectivity are investigated for the triplet pulse sequence with a filtering method. The result shows that the imaging pulse intensity is an important parameter that determines the strength of the effect of nonlinear propagation and that the optimal frequency filtering changes according to it.

Longitudinal comparison of the self-administered ALSFRS-RSE and ALSFRS-R as functional outcome measures in ALS

Objective Test the feasibility, adherence rates and optimal frequency of digital, remote assessments using the ALSFRS-RSE via a customized smartphone-based app. Methods This fully remote, longitudinal study was conducted over a 24-week period, with virtual visits every 3 months and weekly digital assessments. 19 ALS participants completed digital assessments via smartphone, including a digital version of the ALSFRS-RSE and mood survey. Interclass correlation coefficients (ICC) and Bland-Altman plots were used to assess agreement between staff-administered and self-reported ALSFRS-R pairs. Longitudinal change was evaluated using ANCOVA models and linear mixed models, including impact of mood and time of day. Impact of frequency of administration of the ALSFRS-RSE on precision of the estimate slope was tested using a mixed effects model. Results In our ALS cohort, digital assessments were well-accepted and adherence was robust, with completion rates of 86%. There was excellent agreement between the digital self-entry and staff-administered scores computing multiple ICCs (ICC range = 0.925–0.961), with scores on the ALSFRS-RSE slightly higher (1.304 points). Digital assessments were associated with increased precision of the slope, resulting in higher standardized response mean estimates for higher frequencies, though benefit appeared to diminish at biweekly and weekly frequency. Effects of participant mood and time of day on total ALSFRS-RSE score were evaluated but were minimal and not statistically significant. Conclusion Remote collection of digital patient-reported outcomes of functional status such as the ALSFRS-RSE yield more accurate estimates of change over time and provide a broader understanding of the lived experience of people with ALS.

Adaptive HELLO protocol for vehicular networks

In vehicular networks, the update of car Firmware Over The Air (FOTA) is becoming a challenging issue and it mainly relies on topology discovery of neighbouring nodes. Topology discovery in mobile wireless networks is usually done by using HELLO messages. Due to mobility, topology changes occur frequently and must be quickly discovered to avoid routing failures. Since the optimal HELLO frequency depends on parameters that are subject to changes (e.g., speed of nodes, density of nodes), it must be dynamically adjusted to obtain the best trade-off between the network load and the freshness of routing tables. Existing solutions assume random mobility, constant node density and average speed, which do not hold in vehicular networks because vehicles follow specific trajectory patterns (the roads) and density and speed evolve as a function of time (rush hour vs non-rush hour) and area (urban, rural, highway). In this paper, we first draw the specific features of a vehicular network at different times and spaces by analysing real datasets and then propose a dynamic neighbour discovery protocol, Vehicular Adaptive Neighbour discovery Protocol (VANP). VANP is a fully-distributed protocol that sends beacons at an optimal frequency without knowing it a priori. The objective is to reduce the frequency at which HELLO messages are sent to save bandwidth and energy while still preserving the quality of the neighbour discovery. Through extensive simulations run on real datasets, we show that the optimal HELLO frequency can be reached by maintaining a constant optimal turnover, independent from the speed of the nodes and by aiming at this turnover, nodes automatically use the optimal HELLO frequency. Results show that VANP allows the discovery of relevant neighbours by missing at most two neighbours over all scenarios and reducing the number of HELLO messages up to twice, hence saving bandwidth and energy.

Experimental study on identifying the number of wire breaks in prestressed concrete cylinder pipe based on piezoelectric sensing technology

Identifying wire breaks in prestressed concrete cylinder pipes (PCCP) has become an important research topic in recent years. Based on previous numerical studies, this paper presents the first experimental study to identify the number of wire breaks in a PCCP using piezoelectric sensing technology. During the experiment, wire breaks were simulated on a large-diameter embedded DN4000 PCCP and small-diameter lined DN700 PCCP, with a testing device designed to realise the identification method using body stress waves as a medium. Based on the analysis of the output voltage, two types of damage indices were adopted to evaluate the wire break damage. The optimal identification frequencies and corresponding damage indices were determined for different engineering application scenarios. The experimental results are consistent with those of previous numerical simulation studies, further confirming the validity of this technique.