Feasible Parameter Research Articles

Lie-theory-based dynamic model identification of serial robots considering nonlinear friction and optimal excitation trajectory

Abstract Accurate dynamic model is essential for the model-based control of robotic systems. However, on the one hand, the nonlinearity of the friction is seldom treated in robot dynamics. On the other hand, few of the previous studies reasonably balance the calculation time-consuming and the quality for the excitation trajectory optimization. To address these challenges, this article gives a Lie-theory-based dynamic modeling scheme of multi-degree-of-freedom (DoF) serial robots involving nonlinear friction and excitation trajectory optimization. First, we introduce two coefficients to describe the Stribeck characteristics of Coulomb and static friction and consider the dependency of friction on load torque, so as to propose an improved Stribeck friction model. Whereafter, the improved friction model is simplified in a no-load scenario, a novel nonlinear dynamic model is linearized to capture the features of viscous friction across the entire velocity range. Additionally, a new optimization algorithm of excitation trajectories is presented considering the benefits of three different optimization criteria to design the optimal excitation trajectory. On the basis of the above, we retrieve a feasible dynamic parameter set of serial robots through the hybrid least square algorithm. Finally, our research is supported by simulation and experimental analyses of different combinations on the seven-DoF Franka Emika robot. The results show that the proposed friction has better accuracy performance, and the modified optimization algorithm can reduce the overall time required for the optimization process while maintaining the quality of the identification results.

Exploring the repeatability of pulse arrival time in healthy subjects: A test-retest approach

Objectives: Vascular ageing is increasingly being recognised as a vital marker of cardiovascular morbidity and mortality. Assessment of vascular stiffness is an important parameter in this context. Pulse arrival time (PAT) assessed using photoplethysmography (PPG) and digital electrocardiogram (ECG) signals is a feasible and cost-effective parameter for this assessment. However, there are few, if any, studies that have assessed the test-retest repeatability of this parameter over time. Materials and Methods: We computed PAT using finger PPG and Lead II ECG and measured it sequentially at five instances over a period of 1 month in 21 healthy adults (10 males and 11 females). Mean and diastolic blood pressure (MBP and DBP) and heart rate (HR) were also measured at each visit. A novel parameter, PAT normalised for HR of 75 (PAT-75), was also computed. PAT and PAT-75 were compared for these visits using repeated measures analysis of variance. The intraclass correlation coefficient (ICC) was used to assess the test-retest reliability of this parameter. Results: MBP, DBP, and PAT values did not show any difference between the visits. HR was significantly different between the visits. PAT-75 was significantly lower for the afternoon of day 1 as compared to the forenoon. ICC demonstrated only moderate reliability of PAT (ICC = 0.57), with further reduction observed for PAT-75 (ICC = 0.38). Conclusion: PAT was only moderately repeatable on repeated evaluation over a 1-month period. This finding may have implications for the large-scale applicability of this technology, and therefore, we propose further investigation into the repeatability of this parameter in large cohorts.

Real-time flood forecasting and uncertainty analysis: a case study of the Krong H’nang hydropower reservoir

ABSTRACT Early and reliable flood forecasting is crucial for mitigating the impacts of floods and ensuring the safe operation of irrigation and hydroelectric facilities. Traditional methods often use a calibrated event-based rainfall-runoff model with a limited number of simulations, making it difficult to measure parameter uncertainties accurately. This paper introduces a new method for estimating the parameters of the HEC-HMS model and evaluating the uncertainties in real-time flood forecasting. First, the Latin Hypercube Sampling (LHS) procedure is used to efficiently sample the parameter values throughout the feasible parameter space. Next, thousands of parameter sets are simulated using a deterministic rainfall-runoff model, generating numerous initial solutions for the Shuffled Complex Evolution (SCE-UA) algorithm to search and evolve. Additional parameter sets are then generated as the search evolves, leading to new simulations until the algorithm reaches the convergence criteria. The optimal solutions are selected based on predefined multiple objective functions. Uncertainty of the forecast results is also computed using the Generalized Likelihood Uncertainty Estimation (GLUE) method and represented as confidence intervals. The method was applied to forecast flood hydrographs at the Krong H’nang hydropower reservoir in Vietnam, using data from 33 flood events from 2016 to 2021. The results demonstrate that the program can effectively forecast the flood hydrograph up to 4 hours in advance (the Kling-Gupta efficiency KGE > 0.8 and the absolute relative volume error |VE| < 10%). The observed values fall within the uncertainty range of Q5%-Q95%. Compared to the conventional method, which uses a fixed parameter set value, this approach is superior and therefore can assist policymakers and operators in more effectively managing reservoir operations.

Optimization of Connection Parameters of Self-Adaptive Modular Floating Wind Farms

Connection parameters are the key factors influencing the responses of modular floating structures; due to the complexity of structural response properties, the assessment and optimization of connection parameters are still vital issues in designing modular floating structures. In the present work, for a novel structural configuration of self-adaptive modular floating wind farms based on existing works from the case of a mobile offshore base, a quantified approach for the assessment of connection parameters is established based on frequency domain numerical analysis taking into account both the economic effects and generalized performance. Based on the quantified assessment, an optimization process is carried out, to obtain a connection parameter combination. From the optimized connection parameters, it can be found that the most appropriate tri-axial stiffness according to present studies is in the magnitude from 1 × 106 to 7 × 107 N/m, and the damping ratio is close to 1.0 for most connection structures. By contrast with feasible uniform connection parameters, the optimization methodology is confirmed to be able to reduce both connection parameters and responses. Then, a time domain approach for the calculation of motions of interconnected modular floating structures taking into account geometry nonlinearity is proposed and obtained in good accordance with the frequency domain results, and the effectiveness of both the frequency domain and time domain is validated.

Longitudinal echocardiographic parameters for evaluation of pulmonary hypertension in preterm infants with very low birth weight.

Echocardiography is essential for the evaluation of pulmonary hypertension. We determined the feasible quantitative parameter for screening and monitoring pulmonary hypertension in preterm infants. This secondary analysis of a prospective cohort single-centre study was conducted between August 2019 and September 2020. Serial echocardiography was performed 7 and 28 days after birth and at 36 weeks postmenstrual age. The data of infants who developed pulmonary hypertension at 36 weeks postmenstrual age were compared with those without pulmonary hypertension. We also modelled the parameters' trend and performed an interaction test using multi-level Gaussian regression. Out of 30 infants enrolled in the study, 79 echocardiograms were analysed. Left ventricular eccentric index was obtainable in all infants, while tricuspid jet velocity was measurable in 44.1%. Left ventricular eccentric index correlated well with tricuspid regurgitation jet velocity (r = 0.77, P < 0.001). Six infants were diagnosed with newly developed or persistent pulmonary hypertension at 36 weeks postmenstrual age. Serial left ventricular eccentric index showed a significantly different increasing trend in the pulmonary hypertension group (change per day: +0.004; P = 0.090) from the decreasing trend among a non-pulmonary hypertension group (change per day: -0.001; P = 0.041) (P for interaction = 0.007). Right ventricular systolic function and right ventricular isovolumic systolic velocity revealed a reducing trend in the pulmonary hypertension group, which was different from the improving trend in non-pulmonary hypertension infants. Infants with low current weight, low postmenstrual age, and requiring high-flow oxygen therapy at day 28 of life trended to increase the risk of late pulmonary hypertension. Left ventricular eccentric index and right ventricular isovolumic systolic velocity were feasible for assessing pulmonary hypertension and should be incorporated into pulmonary hypertension evaluation. Serial left ventricular eccentric index and right ventricular isovolumic systolic velocity may help predict late pulmonary hypertension and early detection of right ventricular dysfunction.

Feasibility and design of nonlinear negative‐stiffness isolating approach for solid‐rocket‐motor‐type structures

AbstractSolid rocket motor (SRM)‐type structures are popular due to their reliability, considering that service safety during transportation can be improved by applying advanced vibration control technologies. In this study, a negative‐stiffness‐enhanced isolation system (NSeIS) with appropriately designed linear and nonlinear properties was developed to vertically isolate SRMs subjected to transportation‐ and deployment‐induced vibrations. The NSeIS design, based on the combination of a negative‐stiffness device and vertical isolator, involved a clear mechanical model, physical realization, and mechanical properties. Parametric analyses were performed on a typical SRM controlled with a linear and nonlinear NSeIS and a conventional isolation system. Subsequently, a feasible parameter domain and design recommendations were deduced. Finally, design cases for the SRM for time‐domain verification were considered. The results revealed that the NSeIS offers a flexible and enhanced isolating effect through the parallel arrangement of the negative‐stiffness device and conventional isolators. For the motor‐type structure, NSeIS ensures marked enhancements in performance and multiple levels of mitigation effects. Thus, compared with a conventional isolator with the same damping, NSeIS achieves a more substantial negative‐stiffness effect for a large displacement response range owing to its nonlinear property. NSeIS can isolate more vibration‐induced energy, thereby suppressing the interface Mises stress, which is essential for SRM‐type structures.

Estimation of Periodontal Inflamed Surface Area by Salivary Lactate Dehydrogenase Level Using a Test Kit.

Background: Salivary lactate dehydrogenase (LD) levels are a feasible and useful parameter for screening periodontal diseases. The periodontal inflamed surface area (PISA) is useful to clinically assess periodontal diseases. However, PISA is difficult to calculate and PISA-compatible screening kits are required. We aimed to investigate the association between salivary LD levels, using a test kit, and PISA and PISA-Japanese and determine the feasibility and reliability of the salivary LD test kit for evaluation of periodontal status. Methods: This study included 110 patients (66.4% female, median and 25-75 percentiles of age were 66.5 and 53.0-75.0 years, respectively) who visited the Dental University Clinic in Japan. Resting saliva samples were collected from each participant and LD levels were evaluated in real time using a kit featuring an integer scale ranging from 1 to 10. PISA and PISA-Japanese were calculated using periodontal parameters. Results: The median salivary LD level was 4.0. The medians of PISA and PISA-Japanese were 46.9 and 61.0, respectively. Salivary LD levels were positively correlated with the bleeding on probing rate (r = 0.626, p < 0.001), PISA (r = 0.560, p < 0.001), and PISA-Japanese (r = 0.581, p < 0.001). Conclusions: Our results suggest that salivary LD levels assessed using the salivary LD kit showed a significantly positive correlation with PISA and PISA-Japanese. In addition, we developed the PISA estimation formula using salivary LD levels measured with a test kit, sex, and age.

3D melt blowing of Elastollan thermoplastic polyurethane for tissue engineering applications: A pilot study

Scaffolds, in addition to being biocompatible, should possess structural and mechanical properties similar to the natural tissues they intend to replace. Many tissue engineering applications require porous 3D scaffolds characterized by unique microfibrous organization and mechanical anisotropy. Manufacturing process principles and process parameter-biomaterial interactions ultimately govern the properties that can be achieved in the scaffold. In this study, we investigate a recently developed nonwoven scaffold fabrication process, 3D melt blowing (3DMB), for processing Elastollan®, a thermoplastic polyurethane with basic mechanical properties suitable for musculoskeletal tissue engineering. The range of feasible processing parameters was screened and the effects of two sets of critical process parameters (fiber deposition offset and surface velocity of the collector) that produced contrasting scaffold morphologies were assessed. Results showed that scaffolds of Group B that were fabricated at the higher fiber deposition offset (90 %) and higher surface velocity of the collector (6 × 105 mm/min) possessed significantly smaller fiber diameter and higher porosity and degree of fiber alignment along the principal direction of collector rotation during 3DMB (all p < 0.05) compared to Group A scaffolds (fabricated at 50 % offset and 1 × 105 mm/min surface velocity). Although both groups possessed similar tensile stiffness, the elongation at failure was significantly different (p < 0.0001). The higher elongation at failure of Group B correlated with the higher degree of fiber alignment in these scaffolds. In contrast, the more isotropic fibrous organization of Group A contributed to their higher compressive stiffness (p = 0.004). The introduction of NaOH treatment to improve hydrophilicity of the scaffolds resulted in a significant reduction of tensile stiffness of Group A (p < 0.05) but not Group B. This treatment did not significantly affect the elongation at failure or compressive stiffness of both groups. With NaOH-treatment, both groups demonstrated good biocompatibility when seeded with fibroblast cells over 14 days. This study confirms the ability to fabricate via 3DMB, biocompatible, micro-fibrous, Elastollan scaffolds relevant for musculoskeletal tissue engineering.

PULSAR Effect: Revealing potential synergies in combined radiation therapy and immunotherapy via differential equations

PULSAR (personalized ultrafractionated stereotactic adaptive radiotherapy) is a form of radiotherapy method where a patient is given a large dose or “pulse” of radiation a couple of weeks apart rather than daily small doses. The tumor response is then monitored to determine when the subsequent pulse should be given. Pre-clinical trials have shown better tumor response in mice that received immunotherapy along with pulses spaced 10 days apart. However, this was not the case when the pulses were 1 or 4 days apart. Therefore, a synergistic effect between immunotherapy and PULSAR is observed when the pulses are spaced out by a certain number of days. In our study, we aimed to develop a mathematical model that can capture the synergistic effect by considering a time-dependent weight function that takes into account the spacing between pulses. We determined feasible parameters by fitting murine tumor volume data of six treatment groups via simulated annealing algorithm. Applying these parameters to the model we simulated 4000 trials with varying sequencing of pulses. These simulations indicated that if pulses were spaced apart by at least 9 days the tumor volume was about 200 mm3 to 250 mm3 smaller when treated with PULSAR combined with immunotherapy. We successfully demonstrate that our model is simple to implement and can generate tumor volume data that is consistent with the pre-clinical trial data. Our model has the potential to aid in the development of clinical trials of PULSAR therapy.

Stable configuration design for libration point gravitational wave observatory

The Sun-Earth L2 libration point configuration is one of the options for space-based gravitational wave detection. Long-term configuration stability is crucial for high-precision measurements, challenged by the strong nonlinear dynamics of the Sun-Earth three-body system. This paper proposes an efficient design method and determines the feasible parameter domain for the libration point gravitational wave observatory. First, the dynamic model for the libration point configuration is established, and the stability indexes are defined. The sensitive parameters that affect the relative geometric configuration are discussed and the phase angle is found to be the key factor. Then, an efficient design method is proposed, and the procedure is divided into two steps. The phase angle of the Earth phase offset orbit and the libration point configuration are optimized successively. Finally, the proposed method is applied to the LAGRANGE mission concept. The results show that the three stability indexes decrease by 59%, 42% and 23%, respectively. Moreover, a mapping between configuration parameters and stability indexes is established. The feasible parameter domain for the stable libration point configuration is discussed. The feasible amplitudes domain in the x and z directions of the libration point orbit should be less than 6200 km and 42000 km, respectively, to guarantee configuration stability. This research could provide a reference for the stable design and implementation of gravitational wave detection missions utilizing libration point configuration in the future.

Optimized multi-head self-attention and gated-dilated convolutional neural network for quantum key distribution and error rate reduction

ABSTRACT Quantum key distribution (QKD) is a secure communication method that enables two parties to securely exchange a secret key. The secure key rate is a crucial metric for assessing the efficiency and practical viability of a QKD system. There are several approaches that are utilized in practice to calculate the secure key rate. In this manuscript, QKD and error rate optimization based on optimized multi-head self-attention and gated-dilated convolutional neural network (QKD-ERO-MSGCNN) is proposed. Initially, the input signals are gathered from 6G wireless networks which face obstacles to channel. For extending maximum transmission distances and improving secret key rates, the signals are fed to the variable velocity strategy particle swarm optimization algorithm, then the signals are fed to MSGCNN for analysing the quantum bit error rate reduction. The MSGCNN is optimized by intensified sand cat swarm optimization. The performance of the QKD-ERO-MSGCNN approach attains 15.57%, 23.89%, and 31.75% higher accuracy when analysed with existing techniques, like device-independent QKD utilizing random quantum states, practical continuous-variable QKD and feasible optimization parameters, entanglement and teleportation in QKD for secure wireless systems, and QKD for large scale networks methods, respectively.

Nonclassical coincidences of atomic and mechanical excitations

Hybrid systems hold promise to provide an advantage in future quantum technology. Operating such systems outside the classical regime is crucially important to fully realize their potential. We investigate a pulsed quantum nondemolition gate between a cloud of atoms and a mechanical oscillator in distant cavities and demonstrate that this gate is capable of producing nonclassical coincidences of excitations in the disparate subsystems interacting by light. The nonclassicality is justified by evaluation of excitations created simultaneously in both modes beyond any joint classical states of such subsystems. To test the result, we use a nonclassicality witness based on available homodyne tomography of the atomic and mechanical states. Using feasible parameters, we show that it is possible to turn the pulsed dynamics of the state-of-the-art systems into nonclassical coincidences, and illustrate it for the cases of the atom-light, optomechanical, and atom-mechanical hybrid interactions. These tests are necessary to open full investigation of quantum correlations in hybrid systems. Published by the American Physical Society 2024

Constraint based Bayesian optimization of bioink precursor: a machine learning framework.

Current research practice for optimizing bioink involves exhaustive experimentation with multi-material composition for determining the printability, shape fidelity and biocompatibility. Predicting bioink properties can be beneficial to the research community but is a challenging task due to the non-Newtonian behavior in complex composition. Existing models such as Cross model become inadequate for predicting the viscosity for heterogeneous composition of bioinks. In this paper, we utilize a machine learning framework to accurately predict the viscosity of heterogeneous bioink compositions, aiming to enhance extrusion-based bioprinting techniques. Utilizing Bayesian optimization (BO), our strategy leverages a limited dataset to inform our model. This is a technique especially useful of the typically sparse data in this domain. Moreover, we have also developed a mask technique that can handle complex constraints, informed by domain expertise, to define the feasible parameter space for the components of the bioink and their interactions. Our proposed method is focused on predicting the intrinsic factor (e.g. viscosity) of the bioink precursor which is tied to the extrinsic property (e.g. cell viability) through the mask function. Through the optimization of the hyperparameter, we strike a balance between exploration of new possibilities and exploitation of known data, a balance crucial for refining our acquisition function. This function then guides the selection of subsequent sampling points within the defined viable space and the process continues until convergence is achieved, indicating that the model has sufficiently explored the parameter space and identified the optimal or near-optimal solutions. Employing this AI-guided BO framework, we have developed, tested, and validated a surrogate model for determining the viscosity of heterogeneous bioink compositions. This data-driven approach significantly reduces the experimental workload required to identify bioink compositions conducive to functional tissue growth. It not only streamlines the process of finding the optimal bioink compositions from a vast array of heterogeneous options but also offers a promising avenue for accelerating advancements in tissue engineering by minimizing the need for extensive experimental trials.

Prefabricated contoured foot orthoses to reduce pain and increase physical activity in people with hip osteoarthritis: A randomised feasibility trial.

Hip osteoarthritis (OA) is a prevalent and burdensome condition that leads to impaired quality of life and a substantial economic burden. Encouraging physical activity, particularly walking, is crucial for OA management, but many individuals with hip OA fail to meet recommended activity levels. Prefabricated contoured foot orthoses have shown promise in improving hip muscle efficiency during walking in laboratory settings, but their real-world feasibility and efficacy remain uncertain. The aim of this study was to assess the feasibility of conducting a fully powered randomised controlled trial (RCT) to evaluate the effectiveness of prefabricated contoured foot orthoses, prescribed via telehealth, in people with hip OA. This feasibility trial randomised 27 participants with hip OA into two groups: prefabricated contoured foot orthoses or flat shoe inserts. Feasibility outcomes were assessed, including recruitment rate, adherence, logbook completion, and dropout rate. Patient-reported outcomes and accelerometer-measured physical activity were collected as secondary outcomes. While the recruitment rate was low (0.88 people/week), adherence to the intervention (59%), logbook completion (93%), and dropout rates (7%) met or exceeded our predefined feasibility parameters. Participants found the intervention acceptable, and practicality was demonstrated with minor adverse events. Preliminary efficacy testing indicated that prefabricated contoured foot orthoses positively affected physical activity (adjusted mean difference=2590 [260 to 4920] steps/day), with comparable outcomes for hip-related quality of life and pain. This trial supports proceeding to a fully powered RCT to assess the effect of teleheath prescribed prefabricated contoured foot orthoses on physical activity in people with hip OA. National Institutes of Health Trial Registry (NCT05138380).

Detoxification of produced water from oil & gas industries using piperazine immobilized Green Fe nanoparticles

The biggest waste stream in the oil and gas sector is produced water. It is made up of both organic and inorganic wastes, both of which, if untreated, are extremely harmful to the environment. This study aims to use Fe-based nanoparticles in an attempt to detoxify produced water. Fe nanoparticles were prepared using green synthesis approach, and their stability was increased by piperazine immobilisation in a chlorinated environment. Experiments on detoxification were carried out under various circumstances in order to determine the effectiveness of detoxification. Variations in the feasible detoxification parameters, including the, the amount of Green Fe nanoparticles immobilised by piperazine, the pH of the reaction medium, the duration of the detoxification process were found to improve the detoxification efficiency. Using Ultra-violet visual ray spectroscopy and Fourier Transform Infrared Spectroscopy, the properties of the prepared Fe naoparticles were analyzed. Chemical and microstructural properties of the nanoparticles were studied using X-Ray Diffraction Spectroscopy, X-ray photoelectron spectroscopy (XPS), Field Emission-Scanning Electron Microscopy and Transmission Electron Microscopy. Detoxification experiments conducted in photocatalytic environment exhibited detoxification efficiency as high as 89.3 %.

Atom-magnon entanglement in a coupled cavity-magnon atom-optomechanical system

We propose an alternative way to realize macroscopic entanglement between an atomic ensemble and ferrimagnetic magnons in a hybrid cavity-magnon atom-optomechanics, in which a microwave cavity couples to the magnons via magnetic dipole interaction, and simultaneously couples to a standard optomechanical cavity with an ensemble of two-level atoms. We show that in experimental feasible parameters, the optomechanical entanglement can be transferred to the bipartite subsystems, which makes it possible to generate the macroscopic atom-magnon entanglement and genuine tripartite entanglement. We mainly analyze the effects of coupling strengths on the efficiency of the entanglement transfer and the generation of the atom-magnon entanglement. We find that by selecting appropriate coupling strengths, both the degree of the atom-magnon entanglement and its robustness against the environmental temperature are enhanced significantly.

Energy efficient and sustainable design of a multi-story building based on embodied energy and cost

Sustainable multi-story building designs are gaining increasing attention in light of the green development of the building industry. Recently, many studies have been conducted to determine the optimized embodied energy considering size of structural members and materials strength using a single objective function. In this context, the current study adopted a multi-objective function based on cost and Embodied Energy (EE) for the sustainable design of the entire multi-story building. A BuildingEnergy computer program is used to assess the energy consumption performance of a multi-story reinforcement cement concrete building. Based on the proposed method, an analysis is carried out to compare the optimal solutions for multi-story building. Furthermore, a detailed parametric study was conducted to explore the main factors for energy-efficient column and beam design. The results revealed that with a comparison of the most “carbon-friendly” and “cost-friendly” solutions, an added cost of 6–7% can contribute up to a 13% emission reduction. The sectional dimensions, steel rebar, concrete strengths, cost ratio, building height, and eccentricity remarkably influence sustainable design, cost optimization, and minimum carbon emission. Overall, this study could help to define cost-effective and energy-efficient structural members. Eventually, the EE is confirmed to be a feasible parameter for designing more sustainable multi-story RCC buildings.

Uncertainty quantification and data consistency analysis for the development of hydrogen and syngas oxidation model

The exponential growth of contemporary chemical kinetics data coupled with the potential inherent high uncertainty poses significant challenges for developing chemical kinetic models. To obtain a high-quality dataset for the optimization of H2 and syngas oxidation model, this study developed a framework for data consistency analysis and uncertainty analysis of chemical kinetic data. The framework combines simulations based on solving conservation equations, data-driven metaheuristic algorithms, and statistical analysis. Over 2000 experimental data points, including ignition delay times measured in shock tubes, laminar flame speeds, and concentration profiles measured in perfectly stirred reactors and plug flow reactors, were collected and used to construct the experimental dataset. Seventeen parameters of a detailed H2 and syngas oxidation model were selected to build the reaction rate constant (RRC) dataset. The initially estimated experimental uncertainties and RRC uncertainty factors were updated by slack variables in the iterative algorithm. Some high-uncertainty data were identified and excluded from the optimization dataset. The final experimental dataset achieves data consistency, and the feasible parameter set of RRC shows good prediction capability. The experimental data with high uncertainties were highlighted, and the uncertainty sources were analyzed.

A shared-link type wireless power and data simultaneous transfer system based on a series–parallel resonant network

Wireless Power Transmission (WPT) is widely used. In practical engineering applications, the transmitter and receiver of a stable and reliable WPT system need to establish not only a power transmission channel but also a data transmission channel to realize closed-loop control and information interaction. In this paper, a novel simultaneous wireless power and data transfer system based on a series–parallel (SP) resonant network is proposed. The system integrates an SP higher-order resonant network with series carrier injection, which makes power transmission and data transmission share a magnetic coupling channel. The isolation between power and data is realized by exploiting the frequency characteristics of the compensation network, thus realizing efficient power transmission and data transmission. In this paper, accurate and detailed mathematical modeling of the system is conducted, and the gain characteristics of the power transmission channel and the data transmission channel are demonstrated. Meanwhile, the mutual interference between the two channels is analyzed, and a feasible and effective parameter design method is developed. Finally, an experimental prototype with an output power of 16 W and a backward data rate of 100 Kbps is constructed to verify the feasibility of the proposed system and the correctness of the parameter design.

Analisis Kelayakan Usaha Ternak Kambing Gibas Di Desa Nglumber Kecamatan Kepohbaru Kabupaten Bojonegoro

This research aims to analyze the income, profits and feasibility of the gibas goat farming business in Nglumber Village, Kepohbaru District, Bojonegoro Regency. This research used as informants 6 gibas goat entrepreneurs in Nglumber Village, Kepohbaru District, Bojonegoro Regency. The analytical tools used in this research are total production costs, revenues, profits and business feasibility. The results obtained from this research are that the average total production costs incurred are IDR 112,362,000 month, the average revenue obtained is IDR 79,916,667/month, and the average profit obtained is IDR 9,430,461/month. The results of calculating 3 (three) feasibility parameters for 6 gibas goat livestock entrepreneurs in Nglumber Village, Kepohbaru District, Bojonegoro Regency, can be seen that the R/C ratio obtained an average value of 1.3 &gt; 1, the B/C ratio obtained an average value equal to 0.13 &gt; 0, and ROI obtained an average value of 7%. Therefore, the gibas goat farming business in Nglumber Village, Kepohbaru District, Bojonegoro Regency is feasible.