Error Characteristics Research Articles

Decentralized and coordinated scheduling model of interconnected multi-microgrid based on virtual energy storage

The joint coordinated optimization scheduling of multi-microgrid can reduce the risk of accommodation of renewable energy and the operation costs. In this paper, a decentralized and coordinated scheduling method of interconnected multi-microgrid based on virtual energy storage is proposed. Firstly, the microgrid is modelled as a virtual energy storage model, and the demand and supply are packaged into the charge and discharge states of the virtual energy storage model for information privacy of microgrid. Secondly, the probability characteristics of renewable energy prediction error and system flexible resource are used to quantify the operation risk of microgrid and the available charge and discharge power. The decentralized and coordinated scheduling method contains two-levels optimization model to optimize the power of tie-line and virtual energy storage. The upper is the central coordinate controller scheduling model, and the lower is the optimization scheduling model of sub-microgrid. The analytical target cascading is used to decouple the established upper and lower level models for independent optimization and solution. The proposed scheduling model ensures independent operation of each microgrid, and realizes decentralized autonomy and centralized coordinated management of multi-microgrid. Case studies demonstrate the correctness and a well economy of the proposed scheduling method.

Influence and Correction of Wavefront Primary Aberrations for Radio Telescopes using Aberration Theory

Dual-reflector antennas are widely used in astronomical observations and satellite communication. Structural deformations of the reflectors for radio telescopes are inevitable in outside working conditions due to exterior environment loads, which will cause distortion in the surface of the primary reflector and displacement of the subreflector, then lead to gain degradation and misalignment. In this paper, the influence and correction of misalignment in a dual-reflector antenna have been studied. From the perspective of wavefront aberration, a method is proposed to correct the wavefront primary aberration by adjusting the subreflector position. The characteristics of wavefront errors caused by structural deformation of the reflector have been analyzed, and relationships between the position motions of the subreflector and the Seidel wavefront aberrations are derived. The adjustment quantities of the subreflector are also derived. The results show the appropriate positional change of the subreflector in the lateral and axial directions can effectively correct the effects of the tilt and defocus in the primary aberrations caused by antenna structural deformations.

Reducing Medication Errors in Children's Hospitals.

Knowledge of the prevalence and characteristics of medication errors in pediatric and neonatal patients is limited. This study aimed to evaluate the incidence and medication error characteristics in a pediatric hospital over 5 years and to determine whether serial error prevention programs to optimize a computerized physician order entry (CPOE) system reduce error incidence. We retrospectively reviewed medication errors documented between January 2015 and December 2019. A total of 2,591,596 prescriptions were checked, and 255 errors were identified. Wrong dose prescriptions constituted the most common errors (56.9%). Medications with the highest rate of errors were antibiotics/antiviral drugs (36.9%). Oral route medications comprised the highest portion (60.8%), followed by intravenous ones (28.6%). The most common stage for medication errors was physician ordering (93.3%). Junior residents were responsible for most errors (45.9%). Most errors occurred in the pediatric ward (53.7%). In total, 221 (86.7%) errors were near misses. Only 4 errors (1.6%) were considered significant and required active monitoring or intervention. Type of error, stage of error, staff composition, and severity level of errors were significantly related to the number of errors in different years. There was a statistically significant decrease in errors per 100,000 prescriptions across different years after optimizing the CPOE system. The incidence of medication errors decreased with extensive use of the CPOE system. Continuous application of the CPOE optimization program can effectively reduce medication errors. Further incorporation of pediatric-specific decision-making and support tools and error prevention measures into CPOE systems is needed.

French error type annotation for dictation: A platform with automatic error type annotation for French dictation exercises.

Dictation is considered an efficient exercise for testing the language proficiency of learners of French as a Foreign Language (FFL). However, the traditional teaching approach to dictation reduces the instructional feedback efficiency. To remedy this, this study adopts a design-based research approach and builds an automatic error type annotation platform for dictation practice named FRETA-D (French error type annotation for dictation) to pursue intelligent pedagogical feedback for both FFL teachers and students. FRETA-D can automatically identify error boundaries as well as classify the errors into fine-grained error types in learners' dictation texts. FRETA-D features a dataset-independent classifier based on a framework with 25 main error types, which is generalized from French grammar rules and characteristics of frequent learner dictation errors. Five French teachers are invited to evaluate the appropriateness of automatically predicted error types of 147 randomly selected samples, and the acceptance rate reaches more than 85%. Automatic evaluation on 1,009 sentences by comparing with manually labeled references also shows promising results, reaching more than 85% consistency with human judgments. The accessibility of FRETA-D has also been confirmed by 50 Chinese undergraduate FFL learners with different professional backgrounds. FRETA-D facilitates conducting dynamic statistical analysis of learners'error types. And we share the same findings with previous studies that there exist causal links between the dictation errors and learners' mastery of French phoneme and grapheme.

Multi-objective optimization for greenhouse light environment using Gaussian mixture model and an improved NSGA-II algorithm

Research on the optimization and control of greenhouse light environment is of great significance to improve the production efficiency and economic benefits of greenhouse crop. The optimization of greenhouse light environment should not only meet the requirements of crop photosynthesis, but also reduce the energy consumption cost during light supplement. Therefore, in this paper, a multi-objective optimization model of greenhouse light environment was first established, which was aimed at maximizing the photosynthetic rate of crop and minimizing the energy consumption cost. Then, there were errors between the outputs of photosynthetic rate model and the actual values, which led to that the optimization results based on the photosynthetic rate model were not the actual optimal values, so Gaussian mixture model (GMM) was used to describe the error characteristics of photosynthetic rate model. The error compensation of photosynthetic rate model was realized, and it was introduced into the optimization objective, thus forming a multi-objective optimization model of greenhouse light environment after error compensation. In addition, an improved NSGA-II algorithm based on average distance clustering (ADCNSGA-II) was proposed to solve the multi-objective optimization model. The algorithm divided the whole population into several small populations by using average distance, and then selected, crossed, and mutated small populations. This operation could effectively maintain the diversity of Pareto optimal solution set, and further improve the convergence of algorithm. Finally, taking tomato in a solar greenhouse of the experimental base of Shenyang Agricultural University in Northeast China as the research crop, the established model and the proposed optimal regulation method were verified through simulation experiments. The results showed that the RMSE and MAPE of photosynthetic rate model based on error compensation were 0.7641 and 2.6413 respectively, and the CC of the model was 0.9803, indicating that the model has good prediction performance. Moreover, ADCNSGA-II algorithm was used to solve the multi-objective optimization model after error compensation, and the results were compared with those obtained by solving the optimization model before error compensation. The optimization results obtained by solving the optimization model after error compensation were closer to the actual values, which further proved the reliability of the proposed optimal regulation method.

Allele detection using k-mer-based sequencing error profiles.

For genotype and haplotype inference, typically, sequencing reads aligned to a reference genome are used. The alignments identify the genomic origin of the reads and help to infer the absence or presence of sequence variants in the genome. Since long sequencing reads often come with high rates of systematic sequencing errors, single nucleotides in the reads are not always correctly aligned to the reference genome, which can thus lead to wrong conclusions about the allele carried by a sequencing read at the variant site. Thus, allele detection is not a trivial task, especially for single-nucleotide polymorphisms and indels. To learn the characteristics of sequencing errors, we introduce a method to create an error model in non-variant regions of the genome. This information is later used to distinguish sequencing errors from alternative alleles in variant regions. We show that our method, k-merald, improves allele detection accuracy leading to better genotyping performance as compared to the existing WhatsHap implementation using edit-distance-basedallele detection, with a decrease of 18% and 24% in error ratefor high-coverage Oxford Nanopore and PacBio CLR sequencing reads for sample HG002, respectively. We additionally observed a prominent improvement in genotyping performance for sequencing data with low coverage. For 3 coverage Oxford Nanopore sequencing data, the genotyping error rate reduced from 34% to 31%, corresponding to a 9% decrease. https://github.com/whatshap/whatshap.

Empowering high-speed train positioning: Innovative paradigm for generating universal virtual positioning big data

<abstract><p>High-speed trains (HSTs) positioning is a critical technology that affects the safety and operational efficiency of trains. The unique operating environment of HSTs, coupled with the limitations of real data collection, poses challenges in obtaining large-scale and diverse positioning data. To tackle this problem, we introduce a comprehensive method for generating virtual position data for HSTs. Utilizing virtual simulation technology and expert expertise, this method constructs a HST operating simulation environment on the Unity 3D platform, effectively simulating a range of operating scenarios and complex scenes. Positioning data is collected using virtual sensors, while error characteristics are incorporated to emulate real data collection behavior. The contribution of this paper lies in providing abundant, reliable, controllable and diverse positioning data for HSTs, thereby offering novel insights and data support for the evaluation and optimization of positioning algorithms. This method is not only applicable to various routes and scenarios, but also delivers fresh perspectives on data generation for research in other domains, boasting a broad scope of application.</p></abstract>

Magnetic field time-gate displacement sensor based on discrete winding and its error characteristics

Magnetic field time-gate displacement sensor based on discrete winding and its error characteristics

Impact of Vegetation Gradient and Land Cover Conditions on Soil Moisture Retrievals From Different Frequencies and Acquisition Times of AMSR2

Space-borne remote sensing provides great potential for soil moisture (SM) retrieval and emerged as a significant data source for research in land surface dynamics and associated applications. This study compared the error characteristics of SM estimates retrieved from the Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument on board NASA’s Aqua satellite across different vegetation gradients and land cover conditions, at different overpass times and frequencies, to demonstrate their strengths and limitations. Results demonstrate that AMSR2 C-band products outperform AMSR2 X-band products over moderately and densely vegetated conditions due to lower attenuation by the vegetation canopy. Conversely, X-band products performed better than C-band products in barren lands possibly due to uneven sensing depth and microwave emissions from subsurface in C-band. The daytime products have a higher signal-to-noise ratio (SNR) in sparsely and moderately vegetated areas, whereas nighttime products have a higher SNR in densely vegetated areas. When these products are used selectively based on their error characteristics, the probability of obtaining SM with stronger signal than noise can be significantly improved (95%) at the expense of impaired spatial coverage (70%-pixel loss).

Impact of overloading of photovoltaic arrays on the evaluation of photovoltaic power generation forecasts

• Increasing inverter loading ratio decreases mean absolute percent error in forecast. • The benefit is most apparent on clear days. • PV module overloading reduces the effect of over-forecasting of PV output. • PV module overloading affects the value of PV output forecasting technology. Photovoltaic power generation (PV output) forecast is based on solar irradiance forecasts; therefore, an increase in overloading of PV arrays may affect errors in the PV output forecast. To study the impact of overloading of PV arrays on evaluation of PV output forecasts, we compared the estimated and forecasted values of PV output under various overloading conditions and investigated the characteristics of forecast errors resulting from overloading. We used data of actual estimated PV output and forecasted PV output for 2016 to calculate the estimated and forecasted values of overloaded P PV output. Our findings indicate that compared with over-forecasted errors, errors due to under-forecasting undergo higher reduction in both time and magnitude with increasing inverter loading ratio. However, contrary to the initial assumption, the effect of PV module overloading was smaller than expected, which could be attributed to the smoothing effect of PV systems in a large area. PV module and array prices have been decreasing in the long term, and the number of overloaded PV systems is expected to increase worldwide. This study provides useful information for the stable operation of power systems including overloaded PV systems and for improving the economics of PV systems.

Strapdown Vehicle Gravimetry Nonmodel Error Compensation Method

In strapdown vehicle gravimetry, a new phenomenon was discovered by strapdown vehicle gravimetry error model analysis and simulation. That is, after compensating all error terms in the gravity measurement error model, there is still residual error in gravity results, which could not be described by the model. In response to this, multiscenario simulations were carried out to study the characteristics of this residual nonmodel error. Simulations manifest that the nonmodel error has close relationship with the navigation data recorded during strapdown vehicle gravity measurement. On the basis of this, this letter proposed a strapdown vehicle gravimetry nonmodel error compensation method. This method could estimate the nonmodel error by strapdown vehicle gravimetry simulation, employing the real integrated navigation data and the strapdown inertial navigation system (SINS) real trajectory generator. The effectiveness of the proposed method was verified by a real strapdown vehicle gravimetry test in Changsha. Test results show that the repeatability of the repeat lines under 200 s filtering has been improved from 0.51 to 0.41 mGal, 19.6% increase in accuracy. It demonstrates that the proposed method is correctness and validity in real strapdown vehicle gravimetry application.

A New Bivariate Odd Generalized Exponential Gompertz Distribution

The objective of this study was to present a novel bivariate distribution, which we denoted as the bivariate odd generalized exponential gompertz(BOGE-G) distribution. Other well-known models included in this one include the gompertz, generalized exponential, odd generalized exponential, and odd generalized exponential gompertz distribution. The model introduced here is of Marshall-Olkin type [16]. The marginals of the new bivariate distribution have odd generalized exponential gompertz distribution which proposed by[7]. Closed forms exist for both the joint probability density function and the joint cumulative distribution function. The bivariate moment generating function, marginal moment generating function, conditional distribution, joint reliability function, marginal hazard rate function, joint mean waiting time, and joint reversed hazard rate function are some of the properties of this distribution that have been discussed. The maximum likelihood approach is used to estimate the model parameters. To demonstrate empirically the significance and adaptability of the new model in fitting and evaluating real lifespan data, two sets of real data are studied using the new bivariate distribution. Using the software Mathcad, a simulation research was conducted to evaluate the bias and mean square error (MSE) characteristics of MLE. We found that the bias and MSE decrease as the sample size increases.

Обнаружение и синхронизация слабых по мощности шумоподобных сигналов в спутниковой радиосистеме

The problem of joint detection (search) and synchronization of one or several weak complex spread spectrum signals, mismatched on carrier frequency, frequency phase and time delay, in satellite radio system equipment is considered. It is supposed to use a multistage parallel-serial signal detection and synchronization procedure with joint detection and tracking devices for signal parameter changes with formation of their copies in the quasi-coherent receiver. For predetermined values of the characteristics of errors in the estimation of carrier frequencies and time delays of complex spread spectrum signals a method of approximate estimation of the duration of their detection and synchronization in the satellite radio system is developed. It is shown, that at a signal/noise ratio of the order (-10...-40) dB this time duration can make less than 0.5 s at consideration of possibilities of modern methods of processing of signals and the technological decisions used at their realization.

Detection of GPS C/A Code Self-Interference: Monitor Overview and Applicability

<h3>Abstract</h3> Self-interference can cause large errors of up to tens of meters on the GPS C/A code pseudorange measurement. Although the probability of an occurrence of large self-interference errors is small, to enable the use of C/A code phase measurements in high accuracy or safety-of-life applications, a detection or mitigation method is needed. A stressful case of self-interference is modeled on a GPS hardware simulator to investigate monitor performance using real signal results. A summary of contributions in this paper follows. Self-interference pseudorange error characteristics within and mitigation requirements for the Ground Based Augmentation System (GBAS) Approach Service Type D (GAST-D) environment are identified. Existing monitors are evaluated for their response to self-interference and their ability to detect the error based on the GAST-D environment. This includes the potential for misidentification of the error. A novel Frequency Domain Cross-Correlation (FDCC) detector is proposed that can uniquely identify self-interference error with no siting constraints.

Preliminary Analysis of BDS-3 Performance for ARAIM

<h3>Abstract</h3> To support the operation of advanced receiver autonomous integrity monitoring (ARAIM), an integrity support message indicating a minimum performance level of satellite constellation is required for aircraft navigation. With BDS-3 providing worldwide service since July 2020, it is desirable to undertake a detailed study on its signal-in-space range error characteristics and prior fault probabilities for ARAIM. The latest accuracy criteria released by the China Satellite Navigation Office in May 2021 is validated by the 27 MEO and IGSO satellites in orbit from July 2020 to June 2021, in which 10 single satellite faults were identified and analyzed in detail with no constellation fault found. Based on this one-year data, the probability of single satellite faults and constellation faults can be initially set as 8 × 10⁻⁵ and 1 × 10⁻³, respectively, for BDS-3 in ARAIM.

Default Prediction for Loan Lenders Using Machine Learning Algorithms

Credit loans are considered most essential aspect of most financial institutions. All loan mortgagees or lenders are demanding to identify out effective commercial and business approaches to encourage customers to apply their credit loans. There are numerous business patrons who act negatively after their requests got approval. To avert this condition, lenders have to discover some techniques to forecast customer’s behaviors. This resulted to the usage of machine learning algorithms by the financial lending institutions for accessing loan applicants. Despite advancements in automating decision-based loan systems, most existing models do not consider the “early loan repayment” attribute as a factor in resolving this prediction error. In reality, the amendment for preliminary loan reimbursement in model building is obligatory, since a larger numbers of timely loan reimbursement observed during the loan period, reduces default rate. For effective model’s comparison based on accuracy and minimum errors of prediction, six supervised machine learning algorithms i.e. Random Forest, Artificial Neural Network, Classification and Regression Tree, Support Vector Machine, Logistic Regression, and Naïve Bayes were adopted to develop a default prediction models which include the early loan repayment attribute. The models were trained and tested on a loan dataset consisting of attributes with, and without early loan repayment attribute and were evaluated using five performance metrics. The results of the performance evaluation show that models that account for early loan repayment have higher accuracy, recall, precision, Root Mean Square Error and Receiver Operative Characteristics curve values than models trained without the early loan repayment attribute. The Random forest model proofed to be the best predictive model having 93% accuracy, 11% RMSE, 90% precision, 89% recall and 81% ROC value over others models.

Tunable differential phase shifter with low in-band phase deviation error over wide phase shift range

In the brief, a tunable differential phase shifter (D-PS) which features the characteristics of low in-band phase deviation error, wide phase shift range (PSR), and compact structure is presented. The main and reference lines of the D-PS are constructed by reflection-type phase shifters (RTPSs). In the main line, the reflection load is composed of two varactors and a short-circuited stub in parallel connection. While the reflection load in the reference line is consisted of an inductor paralleled with a short-circuited stub. Design equations of the proposed D-PS is derived, and the influences of the reflection loads on the performances of the D-PS are investigated. For validation, a prototype operating at 2 GHz is designed. Measurement results show that the 10-dB impedance matching bandwidth is 20.7 %. During the tuning, a PSR of 243° is obtained and the bandwidth for phase difference error <10° is 12.1 %.

Design and dynamic transmission error analysis of a new type of cycloidal-pin reducer with a rotatable output-pin mechanism

A new type of one-stage precision cycloidal-pin reducer is designed and explored in this study. The design innovatively replaces the fixed output-pin mechanism of conventional cycloidal-pin reducers with a rotatable output-pin mechanism, thereby transforming the sliding contact between the output-pin and the output-hole into a rolling contact. This new structural design is found to significantly improve the transmission efficiency of the reducer. To evaluate the dynamic transmission error (DTE) characteristics of the proposed reducer, a general dynamic model of the cycloidal-pin transmission system considering the influences of multi-source error factors on the geometry of the main components is established. The geometric error of the component is determined by taking random values within a given design-tolerance zone. The geometric error distribution introduced using this method can well match the actual machining situation. Finally, the DTEs of the new reducers with three different tolerance designs are analyzed numerically and tested experimentally. The results show that the new reducer with a reasonable tolerance design can achieve high transmission accuracy and has the potential for application in the joints of industrial robots.

Research on Generating Gear Grinding Machining Error Based on Mapping Relationship between Grinding Wheel Surface and Tooth Flank

This paper proposes a method to study the machining error when one is generating gear grinding based on the mapping relationship between the grinding wheel surface and the tooth flank. The profile of the grinding wheel after grinding is collected, and the theoretical tooth flank is derived according to a model of generating gear grinding. By comparing the normal deviation of the theoretical tooth flank with the measured tooth flank, the machining error characteristics are identified. Firstly, the mathematical model of generating gear grinding is established according to a multi-body theory and coordinate transformation. Secondly, the experiments of the lead modification for helical gear were performed on a YW7232 CNC gear grinding machine. The tooth flank twist compensation function was turned off in experiments No. 1–No. 3, and it was turned on in experiments No. 4–No. 6, while the other process parameters kept the same. Then, the corresponding theoretical tooth flank data were derived from the grinding wheel surface which were measured using the laser profilometer LJ-V7000. Finally, the machining error characteristics were obtained by analyzing the difference between the theoretical and measured tooth flank deviations. The result of this paper can provide theoretical and practical references for the improvement of the gear grinding accuracy and gear modification design.

Evaluation of Six Satellite Precipitation Products over the Chinese Mainland

Satellite precipitation products have been applied to many research fields due to their high spatial and temporal resolution. However, satellite inversion of precipitation is indirect, and different inversion algorithms limit the accuracy of the measurement results, which leads to great uncertainty. Therefore, it is of great significance to quantify and record the error characteristics of different satellite precipitation products for their better application in hydrology and other research fields. In this study, based on CN05.1, which is a set of site–based interpolation data, we evaluated the accuracies of the six satellite precipitation datasets (IMERG–E, IMERG–L, IMERG–F, GSMaP, CMORPH, and PERSIANN–CDR) at different temporal scales (daily, monthly, and yearly) in mainland China for the period from 2001 to 2015. The results were as follows: (1) In terms of mean precipitation, IMERG–F was superior to other data in all areas. IMERG products and PERANN–CDR performed better than other products at all scales and were more suitable for precipitation research in mainland China. Site correction can effectively improve the accuracy of product inversion, so IMERG–F was significantly better than IMERG–E and IMERG–L. (2) Except PERSIANN–CDR, all precipitation products underestimated precipitation in the range of 1–4 mm/day and had a high coincidence with CN05.1 in the range of 4–128 mm/day. (3) The performance of six types of satellite precipitation products in summer was better than that in winter. However, the error was larger in seasons with more precipitation. (4) In the Qinghai–Tibet Plateau, where there are few stations, the inversion of precipitation by satellite products is closer to the actual situation, which is noteworthy. These results help users understand the characteristics of these products and improve algorithms for future algorithm developers.