Elimination Of Errors Research Articles

In control or along for the ride? Lessons for anesthesiologists from air traffic control.

Anesthesia professionals work in an unpredictable, rapidly changing environment in which they are quickly diagnose and manage uncommon and life-threatening critical events. The perioperative environment has traditionally been viewed as a deterministic system in which outcomes can be predicted, but recent studies suggest that the operating room behaves more like a complex adaptive system, in which events can interact and connect with each other in unpredictable and unplanned ways. The increasing complexity of the healthcare environment suggests that the complete elimination of human error is not possible. Complex clinical situations predispose to errors that are the result of high workload, decision making under stress, and poor team coordination. The theory behind complex adaptive systems differs from medicine's traditional approach to safety and highlights the importance of an institutional safety culture that encourages flexibility, adaptability, reporting and learning from errors. Instead of focusing on standardization and strict adherence to procedures, clinicians can improve safety by recognizing that unpredictable changes routinely occur in the work environment and learning how resilience can prevent adverse events. A better understanding of automation, complexity, and resilience in a changing environment are essential steps toward the safe practice of anesthesia.

Causes and conditions of mistakes by participants in criminal proceedings, who have authorities

Purpose. The purpose of the article is a comprehensive study of the phenomenon of mistake. committed by participants in criminal proceedings who have powerful powers, including the causes and conditions of their occurrence. Methods. The methodological basis of the study was a set of general scientific and branch-legal methods, united by an integrated approach, thanks to which it was possible to consider, mistake. The methods of analysis and synthesis, deduction and induction, the formal-legal method, as well as the modeling method made it possible to build a system of conceptual approaches to the problem of the causes and conditions of making mistakes by participants in criminal proceedings who have powerful powers. Results. It was concluded that the concepts of reasons and conditions for the occurrence of errors cannot be equated. The reasons affecting the making of mistakes by the participants in criminal proceedings who have authority are the circumstances or processes that cause and condition the making of mistakes in the process of applying the law by these participants, reducing the effectiveness of law enforcement. At the same time, the conditions for making mistakes by the participants in criminal proceedings, who have powerful powers, do not directly give rise to them, but are a factor that makes it possible to make these mistakes both now and in the future. In particular, they are any shortcomings in the management and organizational activities of these entities. From the point of view of criminal procedural activity, it is difficult to draw a clear distinction between the causes and conditions of making mistakes, because in criminal proceedings there are factors that can be both causes and conditions. Scientific novelty. Attention is drawn to the fact that the activity of eliminating errors by participants in criminal proceedings who have powerful powers requires the development of a concept for solving a complex of theoretical and practical problems of these errors, with the aim of improving the organizational and legal, including criminal procedural error elimination mechanism. Practical significance. The conducted research will contribute to a deeper and comprehensive understanding of this problem, and also provides a basis for the development of effective recommendations to prevent mistakes by participants in criminal proceedings who have powerful powers.

High-Precision Satellite Video Stabilization Method Based on ED-RANSAC Operator

Video image stabilization technology is a crucial foundation for applications such as video image target identification, monitoring, and tracking. Satellite video covers a wide range of areas with complex and similar types of objects on the ground and diverse video types. However, currently, there is a lack of a general high-precision satellite video stabilization method (VSM) that can be applied to different land cover types and imaging modes. This paper proposes a high-precision VSM based on the ED-RANSAC, an error elimination operator constrained by Euclidean distance. Furthermore, a set of accuracy evaluation methods to ensure the reliability of video stabilization are sorted out. This paper conducted video stabilization experiments using optical video data from the Jilin-01 satellite and airborne SAR video data. Under the precision evaluation criteria proposed in this paper, the optical satellite video achieved inter-frame stabilization accuracy of better than 0.15 pixels in different test areas. The overall stabilization accuracy was better than 0.15 pixels. Similarly, the SAR video achieved inter-frame stabilization accuracy better than 0.3 pixels, and the overall stabilization accuracy was better than 0.3 pixels. These experimental results demonstrate the reliability and effectiveness of the proposed method for multi-modal satellite video stabilization.

Elimination of GNSS carrier phase diffraction error using an obstruction adaptive elevation masks determination method in a harsh observing environment

Elimination of GNSS carrier phase diffraction error using an obstruction adaptive elevation masks determination method in a harsh observing environment

A Backstepping Control Strategy for Power System Stability Enhancement

Secure power system operation relies extensively on the analysis of transient stability and control. The dynamics involved in power system control are often complex and nonlinear. Most of the currently existing works approach these frequent problems with nonlinear control techniques, leading to a requirement for specific controller parameter adjustments. In these veins, this paper proposes a new method for stabilizing electric power systems, using nonlinear backstepping control by optimizing the controller’s parameters. The Jaya algorithm and Genetic algorithm are utilized as a powerful meta-heuristic optimization technique to search parameters of an optimal controller. Improvement in system damping, transient stability, and voltage regulation has been achieved by minimizing the integral time absolute error (ITAE) as the objective function. Numerical simulations on an SMIB power system under different fault conditions showed that the proposed method outperforms classical power system stabilizer (PSS) methods, reducing overshoots and settling times and eliminating steady-state errors. These findings highlight the effectiveness of the proposed approach and its potential contribution to the development of advanced nonlinear control techniques for electric power systems. The suggested optimization methods demonstrate superior performance, compared to classical methods, and achieve a reduction of 27.5% in overshoot and 87% in transient time in addition to complete elimination of static error.

TMR sensor current measurement technology for overhead lines

In order to meet the needs of TMR current sensors for overhead line high precision current measurement, a neighboring conductor interference magnetic field error elimination algorithm is proposed. Based on the Biot-Savard law, through the establishment of an interference magnetic field environment mathematical model, the accuracy of the error elimination algorithm is verified in maxwell simulation software. The simulation results show that under the working frequency current, the adjacent wire interference magnetic field elimination algorithm can reduce the error from 14% to less than 1%, and under the lightning wave environment, the error is reduced from 19% to less than 1%. This proves that the proposed algorithm is effective in reducing the measurement error caused by the interference magnetic field of the adjacent conductor.

Wavelet Transform Method for the Evaluation of the Seismic Response of One Isolated Building in the Lima Metropolitan Area

Structural health monitoring based on vibration measurements is a process that implements the instrumentation of sensors and methodologies to provide information regarding the condition of a structure, which allows the evaluation of the safety and integrity of structural systems. Because of this, in the past decades, several algorithms have been developed; among them, the wavelet transform is considered an efficient method for the elimination of the error contained in the acceleration recorded by the sensors. However, due to the complex nature of earthquakes and the particularity of the structural systems, the parameters used by the wavelet transform for error elimination in the seismic response are frequently variable. This paper proposes a method to get the seismic response of a base-isolated building subjected to ground-strong motions through numerical simulations of a mathematical model of the structure, using synthetic records based on historical seismic events occurring in Peru. In this way, the research found that the optimal intrinsic parameters of the building correspond to an approximate frequency interval of 0.20 to 6.25 Hz. Finally, the results show that this method is valid and can be reliably applied in structural health monitoring systems.

An improved attention-based deep learning approach for robust cooling load prediction: Public building cases under diverse occupancy schedules

Space cooling in buildings is responsible for massive energy consumption and carbon emissions. Accurate cooling load prediction can facilitate the implementation of energy-efficiency cooling control strategies in practice. In this paper, an improved attention-based deep learning approach is proposed for robust ultra-short-term cooling load prediction. First, a novel time representation learning is introduced to extract the periodicity and non-periodicity of cooling loads efficiently. Then, long short-term memory with an attention mechanism extracts properly the time steps by identifying the relevant hidden states and learns high-level temporal dependency. The approach additionally incorporates extreme gradient boosting through the error reciprocal method, enhancing the elimination of prediction errors and improving robustness. The study takes Guangzhou as an example and generates cooling loads using diverse occupancy schedules of five building types based on the Chinese National Standard and Typical Meteorological Year data. The approach is evaluated on datasets comprising the cooling loads, meteorological data, and contextual information. Through results analysis, the approach outperforms other models in terms of prediction accuracy and robustness across all building types. Additionally, model interpretation is provided regarding feature importance and attention matrixes, which enhances the understanding and transparency of the final prediction from the proposed approach.

Proposed Algorithm for the Optimisation of the Process of Generating the Geometry of Land Use/Soil Valuation Classes for Land Consolidation

Consolidation of land is one of the main procedures for optimising agrarian structures and creating a space for sustainable rural development. A specific feature of a land consolidation project is its complexity and multiple aspects. The considerable number of complex operations making up the whole procedure implies the necessity of using specialist technical tools to ensure effective surveys. The latest developments in technology are giving way to dedicated solutions that can optimise the working time and quality of the outcomes of respective tasks. This paper outlines a self-designed algorithm for generating the technical layer of land use/soil valuation classes based on layers of soil class contours and land use contours, which are obligatory elements of a digital cadastre database in Poland. The fully automated procedure, next to efficient conversion of spatial data, involves detailed verification of the correctness of input data and elimination of various errors. The tool’s deliverable is a set of data necessary for proceeding with selected elements of the land consolidation process, such as comparative estimates of land value and farmstead designs based on land value. The designed tool was implemented at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów (Poland). The proposed solutions contributed to considerable improvement in the time devoted to performing selected tasks and the substantive correctness of the results.

A Robust Forward Compensated Type-2 PLL Without DC Phase Error During Frequency Ramp for Embedded Magnetic Encoder

To achieve high performance vector control of permanent magnet synchronous machine (PMSM), high precision rotor angle is essential. Compared to traditionally used angle feedback device, e.g., encoder and resolver, the embedded magnetic encoder (EME) achieves high precision angle estimation without extra space occupation by installing several linear Hall sensors into PMSM cavity to monitor the flux leakage and rotor angle. The conventional synchronous reference frame (SRF) phase-locked loop (PLL) can extract phase and frequency from three or two Hall signals simultaneously. Although the type-2 SRF-PLL shows good robust performance against parameter variation, phase error emerges when input frequency changes. More specifically, a DC phase error appears in type-2 SRF-PLL during speed ramp stage due to insufficient order. Increase of the loop order removes the DC phase error but leads to instability risk. In this paper, a novel forward compensation (FC) module is attached on type-2 SRF-PLL to achieve phase error-free when frequency changes, where the instability risk is avoided. The effectiveness of proposed FC module is analytically and experimentally proved, where the phase error elimination, noise immunity and dynamic response are evaluated.

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust and discriminative feature maps is essential for attaining precise pose estimation. Even though the present methodologies established vital progression via feature map’s interlayer fusion and intralevel fusion, some studies show consideration for the combination of these two methodologies. This study focuses upon three phases of pre-processing stages like occlusion elimination, suppression strategy, and heat map methodology to lessen noise within the database. Subsequent to pre-processing errors will be eliminated by employing the quantization phase by embracing the pose detector. Lastly, Image-Guided Progressive Graph Convolution Network (IGP-GCN) has been built for MPE. This IGP-GCN consistently learns rich fundamental spatial information by merging features inside the layers. In order to enhance high-level semantic information and reuse low-level spatial information for correct keypoint representation, this also provides hierarchical connections across feature maps of the same resolution for interlayer fusion. Furthermore, a missing connection between the output high level information and low-level information was noticed. For resolving the issue, the effectual shuffled attention mechanism has been proffered. This shuffle intends to support the cross-channel data interchange between pyramid feature maps, whereas attention creates a trade-off between the high level and low-level representations of output features. This proffered methodology can be called Occlusion Removed_Image Guided Progressive Graph Convolution Network (OccRem_IGP-GCN), and, thus, this can be correlated with the other advanced methodologies. The experimental outcomes exhibit that the OccRem_IGP-GCN methodology attains 98% of accuracy, 93% of sensitivity, 92% of specificity, 88% of f1-score, 42% of relative absolute error, and 30% of mean absolute error.

'Sometimes I feel sad': A qualitative study on children's perceptions with cleft palate speech and language therapy.

Evidence-based speech therapy involves the integration of (1) the scientific evidence for therapy with (2) the perspectives of clinicians concerning therapy and (3) the perspectives of patients about therapy. The cleft literature has already paid attention to the first two cornerstones of evidence-based speech therapy. Much less is known about how children perceive cleft speech therapy. The purpose of the current qualitative study was to investigate the perceptions, emotions and expectations of Flemish-speaking Dutch children with a cleft (lip and) palate (CP ± L), aged 5-12 years, with regard to the speech therapy they receive. In this study, a focus was made on speech therapy to eliminate compensatory cleft speech errors. Six children with a CP ± L, aged between 5 and 12 years, were included in this study. Child-friendly semi-structured interviews were conducted using a participatory, art-based qualitative approach. This means that the 'play and puppets technique' and 'draw-write and photo-elicitation technique' were used to guide the children through the interviews. Data derived from these interviews were analysed using an inductive thematic approach. Trustworthiness of the data was achieved by applying researcher triangulation, negative case analysis and an audit trail. Analyses of the interviews revealed three major themes of importance to the children: (1) treatment values, (2) treatment practices and (3) treatment outcomes. Each theme was divided into different subthemes. The theme 'treatment values' consisted of the subthemes expectations and emotions around therapy and interference with daily living. Information flow, therapy content, confirmation and rewards, parents' attendance, therapy intensity, and homework were subthemes of the major theme 'treatment practices'. The theme 'treatment outcomes' was divided into two subthemes, namely speech improvement and peers' reactions. Most children had positive attitudes towards speech therapy: it was 'something they liked' and 'something fun'. If children had negative attitudes they were related to having a fear of making mistakes during therapy. Children had clear expectations of the purpose of speech therapy. Speech therapy should 'help' improve their speech and make it more understandable to others. The children in this sample made some suggestions to decrease the experienced burden related to speech therapy. The results of this study will help to better tailor speech therapy programmes to the needs and experiences of children with a CP ± L. What is already known on the subject Evidence-based speech therapy involves the integration of (1) the scientific evidence for therapy with (2) the perspectives of clinicians concerning therapy and (3) the perspectives of patients and their families about therapy. The cleft literature has already paid attention to the first two cornerstones of evidence-based speech therapy. Different studies investigated the perspectives of SLPs and parents with regard to cleft palate speech therapy. However, much less is known about the children's own experiences with and perceptions around this speech therapy. What this study adds to existing knowledge This study used a qualitative research design to investigate the perceptions, emotions and expectations of children with a cleft (lip and) palate, aged 5-12 years, with regard to the speech therapy they receive. Speech therapy needed to focus on the elimination of compensatory speech errors. This study provides knowledge on the speech therapy-related experiences of children with a cleft palate. What are the potential or actual clinical implications of this work? Children in this sample made some concrete suggestions to decrease the experienced burden related to cleft speech therapy, for example, integration of school work during therapy sessions and practising on the level of spontaneous speech. The results of this study help us to better tailor speech therapy programmes to the needs and experiences of children with a CP ± L.

Resin Matrix CAD/CAM Materials

CAD/CAM stands for computer-aided design and computer-aided manufacturing. CAD/CAM systems are used to speed up the design and production process in dentistry. With three-dimensional design and milling, various restorations can be fabricated without the need for a physical model. It is possible to scan the oral cavity and take digital impressions. The restoration can be designed with the software's help and fabricated in a shorter time without laboratory stages. In addition, the mechanical strength and edge compatibility of the restorations are improved and the fabrication of aesthetic restorations is aimed. CAD/CAM technology offers advantages such as time savings, elimination of potential errors, ease of use, and treatment quality. With the increasing demand for CAD/CAM restorations, various materials have been developed. Nowadays, CAD/CAM materials are widely available on the market and restorations can be produced from prefabricated blocks and discs. In this review, resin matrix CAD/CAM materials, which are relatively new on the market and claimed to have some positive properties for dental restorations, are described.

Using Artificial Intelligence to Identify Damaged Goods by the External Appearance of the Package when Performing Logistics Operations

A proposed promising method for recognising damaged goods by external appearance of packaging using a learning neural network considers the predicted long-term growth in the volume of transported goods, the increasing influence of economic and territorial factors on transportation processes, the complexity of logistics services and the increase in requirements for their quality, the spread of information technology and the improvement of artificial intelligence tools. The objective of the study is to describe the principles of using an artificial neural network to identify damaged goods by their external appearance. The relevance of the problem is confirmed by data on damage to goods during transportation. The methods used in the study help collecting and analysing data, describing and comparing existing and promising technologies, monitoring and modelling the process of cargo handling, and summarising the results. The analysis of common and promising methods of prevention and detection of cargo damage is backed by the results of research on detecting defects on various surfaces and recognising signs and colours in motion using intelligent technologies. The problems of recognising damages on packaging in complex and unfavourable conditions for machine vision are solved with the help of a convolutional neural network. In accordance with the proposed algorithm, image capture is carried out using standard video surveillance cameras. From the image entered into the neural network, fragments with characteristic features are distinguished, which are further checked for compliance with damage patterns. Following damage contour analysis, the neural network recognises the cargo as damaged. The process of training the neural network and integrating the proposed tool throughout the supply chain ensures the recognition of actually damaged goods and elimination of errors associated with minor permissible damage and packaging features. The proposed concept does not require the installation of additional equipment and does not imply a significant cost of damaged cargo recognition services. The paper offers and describes processes of video recording of the cargo flow, loading an image into a neural network, and a model for recognising damaged cargo by the external appearance of the package.

Modified Fractional Order PID Controller for Load Frequency Control of Four Area Thermal Power System

This paper presents the development of a modified Fractional Order Proportional Integral Derivative (FOPID) controller to mitigate frequency deviation in a four-area thermal power system. Change in load demand and noisy power system environment can cause frequency deviation. Reducing high-frequency deviation is very paramount in load frequency control. This is because large frequency deviation can cause the transmission line to be overloaded, which may damage transformers at the transmission level, damage mechanical devices at the generating stations and also damage consumer devices at the distribution level. The conventional PID has been widely used for this problem. However, the parameter values of the various generating units of the power system like generators, turbines and governors keep changing due to numerous on/off witching in the load side. As such, it is essential that the control strategy applied should have a good capability of handling uncertainties in the system parameters and good disturbance rejection. Fractional order PID controller is known to give a higher phase margin resulting in very good disturbance rejection, robustness to high-frequency noise and elimination of steady-state error. A four-area power system was designed, and FOPID was used as the supplementary controller to mitigate frequency deviation. Ant Lion Optimizer (ALO) algorithm was used to optimize the gains of the FOPID controller by minimizing Integral Square Error (ISE) as the objective function. Results obtained outperformed other designed methods available in the literature in terms of reducing frequency deviation, tie-line power deviation and area control error.

Research on Posture Sensing and Error Elimination for Soft Manipulator Using FBG Sensors

Fiber-optic sensors are highly promising within soft robot sensing applications, but sensing methods based on geometry-based reconstruction limit the sensing capability and range. In this study, a fiber-optic sensor with a different deployment strategy for indirect sensing to monitor the outside posture of a soft manipulator is presented. The internal support structure’s curvature was measured using the FBG sensor, and its mapping to the external pose was then modelled using a modified LSTM network. The error was assumed to follow the Gaussian distribution in the LSTM neural network and was rectified by maximum likelihood estimation to address the issue of noise generated during the deformation transfer and curvature sensing of the soft structure. For the soft manipulator, the network model’s sensing performance was demonstrated. The proposed method’s average absolute error for posture sensing was 63.3% lower than the error before optimization, and the root mean square error was 56.9% lower than the error before optimization. The comparison results between the experiment and the simulation demonstrate the viability of the indirect measurement of the soft structure posture using FBG sensors based on the data-driven method, as well as the significant impact of the error optimization method based on the Gaussian distribution assumption.

Duality-Based Near-Fuel-Optimal Impulsive Trajectory Computation for Spacecraft Rendezvous Under Perturbations

In this study, a novel impulsive trajectory optimization algorithm for near-fuel-optimal rendezvous under perturbations is presented. The algorithm, called algorithm for impulsive rendezvous trajectory optimization under perturbations (AIRTOP), is designed such that the accuracy of rendezvous constraints is improved as much as possible while retaining the first-order optimality, under high-fidelity dynamics models that encompass various orbital perturbations (e.g., nonspherical gravity, air drag, luni-solar gravity, and solar radiation pressure). To eliminate rendezvous constraint errors, AIRTOP solves the linearized impulsive rendezvous problem recursively using the nonsingular dual-primal optimization algorithm. To improve the computational efficiency, AIRTOP applies the approximate analytical gradient of the constraint error norm during its error elimination process. We present three numerical simulations near circular and elliptical orbits. The simulation results show that i) AIRTOP can successfully solve impulsive rendezvous problems under realistic orbital perturbations with minimal user intervention, and ii) it can generate more fuel-efficient solutions in similar or shorter computation time than two other methods, namely, the differential corrector of the General Mission Analysis Tool and the global optimization approach, which can also take complex perturbations into account.

Is challenging testimony a new duty of the accused?

The article discusses the possibility of the court, provided for in paragraph 5 of Part 2 of Article 281 of the Criminal Procedure Code of the Russian Federation, to make a decision on the disclosure of the testimony of witnesses and victims. This problem is investigated by the authors in the context of the fact that the parties should be given the opportunity to protect their interests by all means not prohibited by law, including challenging the read testimony and petitions for their verification with the help of other evidence, as well as by using other means that contribute to the prevention, detection and elimination of errors in court decisions. Based on the study of judicial practice, the authors consider the question of what is meant by the defendant's ability to challenge the testimony of a person testifying against him in ways not prohibited by law and whether it matters what position the defense takes on this issue. The article gives a critical assessment of the approach to solving this issue that has developed in law enforcement practice, which, in essence, "obliges" the defense party to file a petition for a confrontation in case of disagreement with the testimony of a witness. It is noted that this approach is obviously incorrect, and this position is justified. The authors come to the conclusion that depriving the defendant of the right to interrogate the participant showing against him is depriving him of the opportunity to demonstrate to the court the inconsistency of the testimony given by the victim or witness, which can become the key evidence underlying the court's conviction against the defendant. The authors of the article consider correct the position in which the court takes into account the non-confrontation between the accused and the victim, the witness at the stage of preliminary investigation as a circumstance preventing the disclosure of testimony, taking into account the position of the defense. The article evaluates proposals to improve the norms of criminal procedure legislation, taking into account the balance of interests of the parties.

Teneurin trans-axonal signaling prunes topographically missorted axons

Building precise neural circuits necessitates the elimination of axonal projections that have inaccurately formed during development. Although axonal pruning is a selective process, how it is initiated and controlled invivo remains unclear. Here, we show that trans-axonal signaling mediated by the cell surface molecules Glypican-3, Teneurin-3, and Latrophilin-3 prunes misrouted retinal axons in the visual system. Retinotopic neuron transplantations revealed that pioneer ventral axons that elongate first along the optic tract instruct the pruning of dorsal axons that missort in that region. Glypican-3 and Teneurin-3 are both selectively expressed by ventral retinal ganglion cells and cooperate for correcting missorted dorsal axons. The adhesion G-protein-coupled receptor Latrophilin-3 signals along dorsal axons to initiate the elimination of topographic sorting errors. Altogether, our findings show an essential function for Glypican-3, Teneurin-3, and Latrophilin-3 in topographic tract organization and demonstrate that axonal pruning can be initiated by signaling among axons themselves.

Пациенты пожилого и старческого возраста в клинической практике: этические проблемы

Increased life expectancy along with an increasing share of elderly and senile patients in the structure of the population make the tasks of longer healthy life expectancy pressing. A set of activities aimed at optimization of management of patients within the framework of gerontological practice should include elimination and prevention of diagnostic and therapeutic errors. The basic risk factors of medical errors include high heterogeneity of elderly and senile patients, overburdened healthcare system, polypharmacy, including due to parallel prescription of drugs to the same patient by multiple medical professionals, concomitant diseases, and high comorbidity, measured by the Charlson Comorbidity Index. Mismanagement of elderly patients can result both from underestimated severity of the patient’s conditions, and from hyperdiagnostics. Typical errors of pharmacotherapy include use of potentially inappropriate medications, potential prescribing omissions, simultaneous prescription of drugs with high risk of clinically significant interactions, incorrect selection of dosage without taking into account the renal failure, which is associated with high risk of toxic effects. Affordability of medical aid for an elderly patient is another important social aspect influencing the patient’s quality of life. As far as basic ethical principles of management of elderly and senile patients go, it is necessary to respect independence, well-being and justice for the patients regarding possible obtaining of qualitative medical aid as compared with other age groups.