Elimination Of Errors Research Articles

A swarm‐optimized microbial colony counter

AbstractThe identification of bacterial colonies is deemed to be crucial in microbiology as it helps in identifying specific categories of bacteria. The careful examination of colony morphology plays a crucial role in microbiology laboratories for the identification of microorganisms. Quantifying bacterial colonies on culture plates is a necessary task in Clinical Microbiology Laboratories, but it can be time‐consuming and susceptible to inaccuracies. Therefore, there is a need to develop an automated system that is both dependable and cost‐effective. Advancements in Deep Learning have played a crucial role in improving processes by providing maximum accuracy with a negligible amount of error. This research proposes an automated technique to extract the bacterial colonies using SegNet, a semantic segmentation network. The segmented colonies are then counted with the assistance of blob counter to accomplish the activity of colony counting. Furthermore, to ameliorate the proficiency of the segmentation network, the network weights are optimized using a swarm optimizer. The proposed methodology is both cost‐effective and time‐efficient, while also providing better accuracy and precise colony counts, ensuring the elimination of human errors involved in traditional colony counting techniques. The investigative assessments were carried out on three distinct sets of data: Microorganism, DIBaS, and tailored datasets. The results obtained from these assessments revealed that the suggested framework attained an accuracy rate of 88.32%, surpassing other conventional methodologies with the utilization of an optimizer.

A S-shape feedrate scheduling method with rounding error elimination

A S-shape feedrate scheduling method with rounding error elimination

Sliding mode control with higher order strategy for buck converter in the presence of dynamic load

The combination of DC-to-DC converters with DC machines for smooth beginning of DC drives has various practical applications. The Buck converter provides smooth start of the DC motor by applying desired voltage in accordance with the control signal. This paper proposes a Higher Order Sliding Mode (HOSM) based control algorithm for the speed control of Permanent Magnet DC (PMDC) motor with Buck converter under different loaded conditions. This control algorithm minimizes the initial peak current and provides smooth speed control with load changes. The performance of proportional integral derivative sliding surface is compared with classical sliding surface for constant load torque through Matlab simulation. In proportional integral derivative sliding surface (PIDSS), the integral component aids in the elimination of steady-state errors in the variable under control. This is especially useful for systems where it is essential to maintain zero steady-state error. Simulation results indicate the performance of the proposed HOSM control algorithm in achieving the required speed and load variations in finite time.

The role of autonomous vehicles in transportation equity in Tempe, Arizona

In 2016, The National Highway Traffic Safety Administration reported that human error is involved in 94–96% of all motor vehicle crashes. Also in 2016, Bonnefon et al. predicted that autonomous vehicles could eliminate 90% of traffic collisions due to their elimination of human error. However, questions of safety, accessibility, and social equity have arisen after the first pedestrian death by an autonomous vehicle in its testing phase occurred in Tempe, AZ, in 2018. This project analyzes how social equity issues shape the discussion, creation, and implementation of governmental policies and regulations surrounding driverless automobiles in Tempe, using policy and text analysis as well as semi-structured interviews of government officials or residents of Tempe. Informed by the concept of the right to the city and critical legal studies, this research suggests that public policy around autonomous vehicles does create new and expand existing spaces for inequality in Tempe. This is exacerbated by increased awareness of inequality within Arizona’s autonomous vehicle regulation scheme and its entire transportation system after the first pedestrian death by autonomous vehicle.

Best practices in reporting analyses of questionnaires as objective rating scales of variable measures.

The best practice model states that the highest quality of scientific information in a discipline should be used when addressing pertinent problems. The usefulness of any measure depends on the least allowable error, which implies that best practice approaches must be used during analyses of rating scales. However, modern theories of objective measurement in advanced statistics suggest there are some shortcomings in reports of questionnaire analyses. To highlight some common problems in questionnaire data and suggest techniques of constructing objective measures during rating scale analysis. Questionnaires are frequently used as rating scales of latent variables, such as knowledge, anxiety and outcomes of treatments. However, reports of the steps involved before generating the final 'measures' often fail to present known limitations and robust solutions to the problems common to questionnaire data. Most designers of questionnaires generate variable measures for either educational or clinical research purposes without providing adequate explanations of the steps taken to address inherent limitations that may worsen the error terms in the outcome measure. Cursory attention is given to the problems in questionnaire analysis as most users do not convincingly justify the measurement techniques they used before they present variable estimation. Reporting the techniques used to address data complexity by engaging objective measurement parameters ensures best practice and emphasises the credibility of the outcome measure. Among researchers, using the techniques outlined here will lead to standardisation of questionnaire analysis and elimination of avoidable errors in constructing variable measures, resulting in high-quality data suitable for parametric statistics. For clinicians, these methods will simplify the interpretation of numerical measures to equivalent indicators on Wright maps, thus avoiding inconsistencies and misinterpretations of variable measure.

Drift Error Compensation Algorithm for Heterodyne Optical Seawater Refractive Index Monitoring of Unstable Signals.

The refractive index measurement of seawater has proven significance in oceanography, while an optical heterodyne interferometer is an important, highly accurate, tool used for seawater refractive index measurement. However, for practical seawater refractive index measurement, the refractive index of seawater needs to be monitored for long periods of time, and the influence of drift error on the measurement results for these cases cannot be ignored. This paper proposes a drift error compensation algorithm based on wavelet decomposition, which can adaptively separate the background from the signal, and then calculate the frequency difference to compensate for the drift error. It is suitable for unstable signals, especially signals with large differences between the beginning and the end, which is common in actual seawater refractive index monitoring. The authors identify that the primary cause of drift error is the frequency instability of the acousto-optic frequency shifter (AOFS), and the actual frequency difference was measured through experimentation. The frequency difference was around 0.1 Hz. Simulation experiments were designed to verify the effectiveness of the algorithm, and the standard deviation of the optical length of the results was on the scale of 10-8 m. Liquid refractive index measurement experiments were carried out in a laboratory, and the measurement error was reduced from 36.942% to 0.592% after algorithm processing. Field experiments were carried out regarding seawater refractive index monitoring, and the algorithm-processing results are able to match the motion of the target vehicle. The experimental data were processed with different algorithms, and, according to the comparison of the results, the proposed algorithm performs better than other existing drift error elimination algorithms.

Single-shot experimental-numerical twin-image removal in lensless digital holographic microscopy

Lensless digital holographic microscopy (LDHM) offers very large field of view label-free imaging crucial, e.g., in high-throughput particle tracking and biomedical examination of cells and tissues. Compact layouts promote point-of-case and out-of-laboratory applications. The LDHM, based on the Gabor in-line holographic principle, is inherently spoiled by the twin-image effect, which complicates the quantitative analysis of reconstructed phase and amplitude maps. Popular family of solutions consists of numerical methods, which tend to minimize twin-image upon iterative process based on data redundancy. Additional hologram recordings are needed, and final results heavily depend on the algorithmic parameters, however. In this contribution we present a novel single-shot experimental-numerical twin-image removal technique for LDHM. It leverages two-source off-axis hologram recording deploying simple fiber splitter. Additionally, we introduce a novel phase retrieval numerical algorithm specifically tailored to the acquired holograms, that provides twin-image-free reconstruction without compromising the resolution. We quantitatively and qualitatively verify proposed method employing phase test target and cheek cells biosample. The results demonstrate that the proposed technique enables low-cost compact LDHM imaging with enhanced precision, achieved through the elimination of twin-image errors. This advancement opens new avenues for more accurate technical and biomedical imaging applications using LDHM, particularly in scenarios where cost-effective and portable imaging solutions are desired.

RECOMMENDED TECHNOLOGY FOR TOMOGRAPHIC INSPECTION IN THE LABORATORY

Paper presents a detailed technology of tomographic inspection in the laboratory. Tomographic inspection is a powerful tool for obtaining high-quality three-dimensional images of the internal structure of objects. The advantages of the method are considered, which include the non-destructive nature of the control, high resolution, measurement accuracy, and the ability to detect defects invisible to the human eye. The main attention is paid to the description of the main stages of tomographic inspection, which are recommended to achieve maximum efficiency. Possible errors that may occur during tomographic inspection in the laboratory are highlighted, and ways to eliminate them are provided. The optimal parameters that should be taken into account during tomographic inspection are considered, including the correct choice of tomograph parameters, setting of lighting conditions, and correct positioning of the object under inspection. The process of processing the obtained inspection data is described in detail, which helps to ensure high-quality information analysis. The authors also analyze the feasibility of the control stages, comparing the results obtained at different stages and considering their impact on the final result. This work is a valuable source of information for specialists involved in tomographic control in the laboratory. The described technology and recommendations will help to improve the quality and efficiency of tomographic inspection in their work. The research results presented in this article can improve the inspection process, reduce errors, and detect even the smallest defects in samples. In general, this paper offers a recommended technology for tomographic inspection in the laboratory, taking into account key aspects such as the advantages of the method, inspection stages, error elimination, optimal parameters, object positioning, and data processing. Taking these recommendations into account, specialists will be able to provide more accurate, efficient and reliable tomographic control in their work. Thus, this article will be a valuable addition to the scientific literature in the field of non-destructive testing, will help improve the quality of tomographic testing and promote the development of this important method in the laboratory.

Membership-Function-Based Secondary Frequency Regulation for Distributed Energy Resources in Islanded Microgrids With Communication Delay Compensation

Secondary frequency control is one of the most effective measures to ensure the stable operation of islanded microgrids (MGs). Most research on secondary frequency regulation has only focused on realizing steady-state operation objectives, that is, frequency restoration and power sharing. However, improving the dynamic performance of secondary frequency control is of great importance, especially in synchronous distributed energy resources. These synchronous units can introduce undesired oscillation modes, which may cause the instability conditions of MGs. To improve the dynamic performance of islanded MGs, a membership-function (MF) -based control strategy is proposed. The proposed strategy can trade-off between transient frequency regulation and frequency error elimination using the MF values calculated by the time-stamped synchronized measurements of distribution-level phasor measurement units. Besides, considering the time-varying communication delays in secondary frequency control loops, an adaptive delay compensator is proposed. The weights of the proposed compensator are updated by real-time delay measurements to compensate for the phase lag of control signals. Therefore, the adverse effect of communication delays on secondary frequency control is weakened effectively. Numerical simulations on an IEEE 34-bus system and a typical 40-bus islanded MG system demonstrate the advantages of the proposed method in the secondary frequency regulation of islanded MGs.

Correction to: A novel feed rate scheduling method with acc-jerk-continuity and round-off error elimination for non-uniform rational B-spline interpolation

Correction to: A novel feed rate scheduling method with acc-jerk-continuity and round-off error elimination for non-uniform rational B-spline interpolation

A Railway Track Extraction Method Based on Improved DeepLabV3+

Extracting railway tracks is crucial for creating electronic railway maps. Traditional methods require significant manual labor and resources while existing neural networks have limitations in efficiency and precision. To address these challenges, a railway track extraction method using an improved DeepLabV3+ model is proposed, which incorporates several key enhancements. Firstly, the encoder part of the method utilizes the lightweight network MobileNetV3 as the backbone extraction network for DeepLabV3+. Secondly, the decoder part adopts the lightweight, universal upsampling operator CARAFE for upsampling. Lastly, to address any potential extraction errors, morphological algorithms are applied to optimize the extraction results. A dedicated railway track segmentation dataset is also created to train and evaluate the proposed method. The experimental results demonstrate that the model achieves impressive performance on the railway track segmentation dataset and DeepGlobe dataset. The MIoU scores are 88.93% and 84.72%, with Recall values of 89.02% and 86.96%. Moreover, the overall accuracy stands at 97.69% and 94.84%. The algorithm’s operation time is about 5% lower than the original network. Furthermore, the morphological algorithm effectively eliminates errors like holes and spots. These findings indicate the model’s accuracy, efficiency, and enhancement brought by the morphological algorithm in error elimination.

A new algorithm for investigating strongly correlated systems using Hubbard model

In this work, a new algorithm introduces for calculating the average Green function of an interacting system that obeys the Hubbard model. This algorithm is applied to investigate the effects of onsite repulsion on the band structure of a square lattice in both the single-site approximations such as dynamical mean field theory (DMFT) and multi-site approximations such as effective medium supercell approximation (EMSCA). The advantages of our algorithm in comparison to the Hirsch-Fye algorithm and also the Blankenbecler, Scalapino, and Sugar (BSS) algorithm are the elimination of instabilities resulting from the Metropolis algorithm in the accepting and rejecting configurations, stability at low temperatures, the elimination of systematic errors resulting from the update of the Green's function in the quantum Monte Carlo process, and considering different probabilities for each possible configuration. Finally, by using our algorithm, it is possible to calculate the interacting three-dimensional system's band structure and the density of states that obey the Hubbard model. We have applied our algorithm to an interactive two-dimensional square lattice. As a result, phase transition boundaries can be easily recognized through calculated bands for different repulsions. Our results show that critical Coulomb repulsion values for Mott transition are uc = 9.05t and uc = 2.4t for DMFT and BEMSCA respectively. This means that DMFT significantly overestimates band splitting due to electrons' Coulomb repulsion. We found by starting at low repulsions and then increasing electrons' Coulomb repulsion, a partially flatted valence band around the center of the first Brillouin zone appears, but disappears at high repulsions.

Radiographers’ Perspectives on the Impact of Artificial Intelligence use on their future roles: A Qualitative Study

Introduction: The advent of artificially intelligent systems in the field of medical imaging has attracted a lot of attention and sparked a lot of discussion regarding the future roles of radiographers. It is widely believed that Artificial Intelligence (AI) will revolutionize the entire medical imaging field in the near future and alter the current practice of radiographers. Aim: The aim of the study was to explore Zimbabwean radiographers’ perspectives on the impact of AI use on their future roles. Methods: A qualitative explorative design employing in-depth interviews to explore the perceptions of radiographers towards AI use in medical imaging. The study recruited 10 participants and the study was conducted at 5 hospitals in Harare, 2 government and 3 privatehospitals. The interview data was then analyzed using thematic analysis according to Braun and Clarke. Results: Four themes emerged from the interview data. The themes include; Reduce roles of radiographers, Elimination of human errors, Expansion of knowledge and AI will promote radiography. Conclusion: Radiographers must be trained and have underpinning knowledge of AI.This study recommends that AI use should be included in the curriculum of radiography students.

Practice of the European Court of Human Rights as a Means of Preventing and Eliminating Judicial Error in Law Enforcement

In the study special attention was focused on consideration of such integral partst of the right to a fair trial, enshrined in clause 1 of Art. 6 of the Convention, as (a) the right to access to justice, (b) the principle of finality of judgement (“res judicata”) and (c) the standard of judicial independence and impartiality. Based on the examples of decisions of the ECtHR, it is concluded that these components are the basis of judicial activity in general and the behavior of judges that contribute to the prevention and elimination of judicial errors. The author supports the opinion that the above mentioned elements of the right to a fair trial are prerequisites for public confidence in the judiciary and the affirmation of justice in the sense of the legality of a court decision and moral consciousness. The article highlights the main reasons that influence judges to make various mistakes in their activities, such as: disagreements in judicial practice caused by the judges' misunderstanding of the content of the law or the existence of gaps in the legislation, significant violations of procedural law by judges due to their ignorance, or due to the abuse of the judges’ powers conferred on them by national law, external interference in the judge's activities and influence on him that are done for the purpose of giving advantage to one of the parties. The article argues that the Strasbourg Court expresses different positions regarding the stability of judicial practice. However, the author of the article is of the opinion that the unity of practice, that forms a common legal understanding of the same norms, contributes to the minimization of judicial errors, as well as compliance with the principle of "reasonable terms". In addition, the author expresses the position that the standard of finality of court decisions, that is mentioned in the ECtHR decisions, should not depend on the duration of the disputed legal relationship, since this leads to the spread of judicial errors in the application of law by lower courts. The article emphasizes that according to the practice of the European Court, in order to avoid any doubts about the judge's self-interest he/she must take all measures to eliminate such concerns. Otherwise, the judge concerned should be removed from further consideration of such a case. It is noted that this is also a requirement of the judge's integrity according to Art. 3 of the Code of Judicial Ethics. Taking into account all the above-mentioned considerations, it was concluded that the observance of convention rights and principles reflected in the decisions of the ECtHR guarantees judicial activity conducted by national courts with a minimum tolerance of judicial errors in law enforcement, and also confirms the high standards of behavior of Ukrainian judges during their consideration of cases. Key words: judicial error, enforcement, law, convention norms, decision, ECtHR, standard.

Neuroadaptive Control for Complicated Underactuated Systems With Simultaneous Output and Velocity Constraints Exerted on Both Actuated and Unactuated States.

Due to limited workspace and safety requirements for practical underactuated mechanical systems, it is necessary to restrict all to-be-controlled variables and their velocities within preset ranges, avoid collisions/overshoots, and improve braking performance. However, due to fewer available control inputs, it is quite challenging to ensure error elimination and full-state constraints for both actuated/unactuated variables, including displacements/angles and their derivatives (i.e., velocity signals) together. To handle the above issues, this article designs a new adaptive full-state constraint controller for a class of uncertain multi-input-multi-output (MIMO) underactuated systems. First, different output constraint-related auxiliary functions are constructed in the Lyapunov function candidate to generate nonlinear displacement-/angle-limited terms to control all state variables. Then, this article handles velocity constraints in a new manner, where the elaborately designed velocity constraint-related terms are directly introduced into the presented controller (instead of the Lyapunov function candidate), and strict theoretical analysis is provided by utilizing reduction to absurdity. Hence, both actuated and unactuated velocity constraints are ensured to further improve transient performance. In addition, the impact of model uncertainties is addressed online to realize accurate positioning control for all state variables. Compared with current studies of underactuated systems, this article presents the first adaptive controller to address output and velocity constraints for actuated and unactuated variables together; moreover, their asymptotic convergence is proven by strict stability analysis, which is important both theoretically and practically. In the end, the feasibility and robustness of the proposed controller are verified by hardware experiments.

Radio Frequency Identification (RFID) Based Library Management System

Purpose: The aim of this project is to design and build a library management system based on radio frequency identification that will help the librarian manage the shelves with less human involvement.
 Methodology: A dc supply at +5volts was connected to the microcontroller, with a voltage of +12volts dc connected to the buzzer, and a step-down transformer was used to convert 220volts to 5volts in this system. This power supply was connected to the switch, and by pressing a switch button, the current passed through the entire circuit. RFID collects all the data from the RFID tag. Using a UART module, the EM-18 RFID reader module was connected to 5v pic microcontrollers. The EM-1 RFID reader will read the tag number from an RFID tag when it is placed in its field of operation and output the information via a TX terminal. In order to signal successful tag detection, the beep terminal will turn low. Once the card is in front of the RFID reader, the student extracts the data from it and compares it to the data that is stored in the microprocessor, which is coded using embedded c language. If the data matches, the information is shown on the LCD.
 Finding: A library management system based on radio frequency identification and detection (RFID) was developed in this study to improve library use and management. To efficiently identify and manage the books, it will make use of the RFID reader. The student can search the database and, if the book is available, pick it up from the library because the database displays the book's availability at the library. The main advantages of this project in libraries include time savings, quick access to books, and the elimination of manual errors.
 Unique Contribution to Theory, Practice and policy: Every inventive technical design has its limits. This passive RFID-based library management system has some limitations as a technology for precise data collection. This study recommend that the RFID reader should be improved so that it has finger and thumb print access, which is needed to access student data and details. However, it should also include a facial recognition application, which would further strengthen the biometric security of the system and protect it from impersonation by careless students.

Spatially Variant Error Elimination for High-Resolution UAV SAR with Extremely Small Incident Angle

Airborne synthetic aperture radar (SAR) is susceptible to atmospheric disturbance and other factors that cause the position offset error of the antenna phase center and motion error. In close-range detection scenarios, the large elevation angle may make it impossible to directly observe areas near the underlying plane, resulting in observation blind spots. In cases where the illumination elevation angle is extremely large, the influence of range variant envelope error and phase modulations becomes more serious, and traditional two-step motion compensation (MOCO) methods may fail to provide accurate imaging. In addition, conventional phase gradient autofocus (PGA) algorithms suffer from reduced performance in scenes with few strong scattering points. To address these practical challenges, we propose an improved phase-weighted estimation PGA algorithm that analyzes the motion error of UAV SAR under a large elevation angle, providing a solution for high-order range variant motion error. Based on this algorithm, we introduce a combined focusing method that applies a threshold value for selection and optimization. Unlike traditional MOCO methods, our proposed method can more accurately compensate for spatially variant motion error in the case of scenes with few strong scattering points, indicating its wider applicability. The effectiveness of our proposed approach is verified by simulation and real data experimental results.

Elimination of Human Error in Critical Point Drying Process in Plant Tissue Preparation for Electron Microscopy.

Elimination of Human Error in Critical Point Drying Process in Plant Tissue Preparation for Electron Microscopy.

BDS Dual-Frequency Carrier Phase Multipath Hemispherical Map Model and Its Application in Real-Time Deformation Monitoring.

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by applying the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, we propose a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of "zero mean" and divides the appropriate grid density of GEO and IGSO/MEO, respectively, to construct a dual-frequency multipath hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multipath error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates are 1.7 mm and 4.6 mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60%, respectively. The fixed rate of ambiguity increased by 5-7%.

Phase-Locked Synthetic Wavelength Interferometer Using a Femtosecond Laser for Absolute Distance Measurement without Cyclic Error.

We present a phase-locked synthetic wavelength interferometer that enables a complete elimination of cyclic errors in absolute distance measurements. With this method, the phase difference between the reference and measurement paths is fed back into a phase lock-in system, which is then used to control the synthetic wavelength and set the phase difference to zero using an external cavity acousto-optic modulator. We validated the cyclic error removal of the proposed phase-locked method by comparing it with the conventional phase-measuring method of the synthetic wavelength interferometer. By analyzing the locked error signal, we achieved a precision of 0.6 mrad in phase without any observed cyclic errors.