Error Factors Research Articles

Medication error in the provision of healthcare services

Medication errors are the most common and widespread medical adverse event that occurs in healthcare settings and can lead to increased patient morbidity, mortality, and healthcare costs. The availability of a wide range of over-the-counter and prescribed medications in the healthcare market, which the general public seems to use on a frequent basis to treat their health complications, has rapidly increased the chances of medication errors. Furthermore, the medication chain has several steps that require different people, and errors can occur at different stages in patient care, from ordering the medication to the time the patient is administered the drug. So each stage of the medication chain is exposed to risks that could result in medication errors. Thereby, medication errors prompt patient harm, preclude immediate discharges, and enhance healthcare costs. As a result, it is important to set up a medication safety culture that can light up in the context of effectively putting strategies into action, and everyone's collaboration and participation to adhering to medication safety strategy can improve patient safety. This review of the literature aims to provide a concept of medication errors, explore the pattern of errors, causes and consequences of errors, and error-related adverse events in all types of healthcare settings, risk factors for medication errors, and strategies to avoid and minimize medication errors.

Theoretical Prediction of the Reaction Probabilities of H, O, and OH Radicals on the Polypropylene Surface.

To determine the H-abstraction reaction probabilities of H/O/OH radicals with a polypropylene (PP) surface, a first-principles calculation was performed based on the DLPNO-CCSD(T)/CBS//M06-2X-D3/def-TZVP theory level. The PP chain model used in this study was 2,4,6-trimethylheptane. The rate constants of the H/O/OH radicals with the isolated PP chain model were calculated based on the conventional transition-state theory. By comparing the experimental values and considering the error factors and their compensation, it was concluded that the orders of magnitude of the predicted rate constants were accurate. The resulting rate constants were converted to reaction probabilities between the H/O/OH radicals and the PP surface. The method used in this study is applicable for obtaining theoretical values of surface reaction probabilities based on first-principles calculations. The calculation at the DLPNO-CCSD(T)/CBS theory level has high accuracy but consumes a large amount of computational resources. The study also demonstrated that the double-hybrid functionals, wB97x-2-D3(BJ) and rev-DSD-PBEP86-D3(BJ), with a 3-ζ or 4-ζ basis set, could reproduce the electronic energy values obtained from DLPNO-CCSD(T)/CBS while using only approximately 1/100 of the computational resources required by the latter under our computer configuration.

Object Detection for Safety Attire Using YOLO (You Only Look Once)

Personal protective equipment (PPE) usage is mandated for all employees to prevent workplace accidents and foster a safe and healthy work environment. Using YOLOv8 machine learning and Google Colab's web-based development environment, this research aims to create an immediate detection system for PPE violations in the workplace. By keeping track of PPE compliance, the system is intended to increase workplace safety and prevent accidents. The dataset is collected through a mixture of real-life image gathering and internet datasets. Various images are collected that aim to train the model to detect objects from afar, close, and individually. The research methodology includes a review of the literature, the gathering, pre-processing, and training of models. According to the use of safety helmets, safety shoes, and gloves, there are three different classes of detection based on the bounding box. The system successfully detected the classes with an overall score above 0.8. The safety helmet achieved 0.969, the safety gloves achieved 0.857, followed by the safety vest with 0.887. The findings from this study indicate that the developed system can effectively improve occupational safety and health management. However, there is a detection error factor caused by the lighting and colors. Future research can focus on integrating the system with other work safety systems to provide a comprehensive solution for accident prevention.

Performance analysis of OSSK-UWOC systems considering pointing errors and channel estimation errors.

In this paper, we present the bit error rate (BER) performance of the underwater wireless optical communication (UWOC) systems using the optical space shift keying (OSSK) on the gamma-gamma turbulent fading channel, which also considers pointing errors and channel estimation errors. Firstly, we develop the new expressions for the probability density function (PDF) based on the Gamma-Gamma distribution with error factors. Subsequently, we analyze the statistical characteristic of the difference in attenuation coefficients between two channels in the OSSK system, by which we provide analytical results for evaluating the average BER performance. The results show that the effective improvement of spectral efficiency (SE) and BER performance is achieved by rationally allocating the number of lasers and detectors in the system. The OSSK-UWOC system performs better when a narrow beam waist is used. Furthermore, the presence of channel estimation error brings the BER performance advantage to the system, and the system with a high channel estimation error (ρ = 0.7) shows a 4 dB improvement in signal-to-noise ratio (SNR) gain compared to the system with a low channel estimation error (ρ = 0.95). The findings in this paper can be used for the UWOC system design.

Stepless space-regulation of topological acoustic controller with high fault tolerance

In this paper, the stepless space-regulation of topological acoustic transmission channels with high fault tolerance is proposed through introducing structural defect dislocations into a topological acoustic controller. Due to the stability of topological order against local disturbance, the acoustic wave transmission is immune to dislocation boundaries with strong stability, and thus the topological acoustic controller has high fault tolerance. By continuous changing the dislocation, the position relationship between the outgoing and incident acoustic signals no longer limited to the integer multiple distance related to the lattice size, and can realize the efficient acoustic energy transmission without energy loss at the fractional multiple distance, that is, the topological controller can realize lossless acoustic energy transmission and reception in arbitrary position relationship. Furthermore, the coupling relationship between the defect dislocation and the topological acoustic channel is explored, which can realize the stepless space-regulation of the lossless channel in the wide band range. In addition, by further introducing multi-layer continuous dislocations, this high-fault-tolerant topological acoustic controller still has strong stability, and multiple error factors do not affect the transmission results, which greatly reduces the difficulty of manufacturing. Finally, the stepless space-regulation of topological acoustic channels and the high-fault-tolerant topological acoustic controller that are easy to manufacture are verified by our experiments. This research paves the way for the engineering applications of acoustic micro-control, micro-nano fabrication, remote acoustic energy transmission manipulation, acoustic measurement, weak signal processing, acoustic flexible control and other micro-shape and multi-functional acoustic devices, and will bring more inspiration to other classical wave communication fields such as light wave, electromagnetic wave and so on.

Interpretable spatial-temporal attention convolutional network for rainfall forecasting

The interpretability of rainfall forecasting models is a major challenge in the field of artificial intelligence. Its importance is equal to the evaluation of model accuracy. Owing to the uncertainty and nonlinearity of the rainfall forecasting process, existing hydrological rainfall forecasting models often have low prediction robustness, and the machine learning method ignores the influence of physical factors in the surrounding areas; thus, the physical interpretability of the model is inferior. This study proposes an interpretable spatial-temporal attention convolution network for rainfall interval forecasting (IDSTA-TCN). To analyze and mine the uncertainty of input data more effectively, we enhanced a variational mode decomposition (EBO-VMD) algorithm based on Bayesian optimization to decompose the input data. To improve the performance of the original temporal convolution network (TCN) unit in rainfall forecasting and to effectively use the spatial-temporal information of rainfall forecasting data, we improved the spatial-temporal attention mechanism, dynamically combined the geographical information of the meteorological stations in the surrounding area to assist the network unit in better mining the nonlinear impact of historical input information on current rainfall forecasting, and improved the prediction performance of the IDSTA-TCN model. Finally, we designed a more reasonable error factor adjustment interval output strategy to better quantify the impact of prediction errors on the rainfall interval prediction results. Moreover, we conducted a series of experiments to compare and analyze the accuracy of each model according to the most commonly used evaluation indicators in the field of rainfall forecasting. The results demonstrate that the proposed IDSTA-TCN model is superior to the baseline models in most cases. We preliminarily analyzed the spatial-temporal attention weights, which explained the physical rationality of our model.

Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight.

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.

MODEL REGRESI LINIER PENGARUH STANDAR TEKNIS JALAN TERHADAP KECELAKAAN LALU LINTAS PADA JALAN PROVINSI (STUDI KASUS : RUAS JALAN PEMALANG – PURBALINGGA)

In the 2016-2021, there were 12 accidents with 22 deaths and 107 injuries on the Pemalang – Purbalingga road section. One of the factors causing accidents is the lack of attention to infrastructure that meets safety aspects. Even though the number of accidents caused by infrastructure is relatively small when compared to the human error (human) and vehicle (facility) factors, serious attention must still be paid. Traffic accidents caused by a lack of road infrastructure are generally caused by an inaccurate road geometric design, poor road surface conditions, lack of visibility and so on. Therefore the research aims to find accident-prone locations, the causes of accidents from the standard values of road technical requirements and accident regression models. The results of this study. Segments that are categorized as accident-prone locations are STA 32+000, 34+000, 36+000, 47+000 and 48+000. Substandard grades will be the cause of traffic accidents based on road technical requirements. The regression model that can be used to predict the number of accidents on provincial roads according to the variables examined in this study is: Y = -2.618 + 0.049 Grade – 0.019 X Slope – 0.008 H Curv – 0.417 V Curv + 0.264 road width + 0.081 condition IRI roads + 0.014 PCI Road Conditions

On-Machine Calibration of Pitch Deviations of a Linear Scale Grating by Using a Differential Angle Sensor

A differential angle sensor is newly developed to calibrate the pitch deviations of a linear scale grating with a nominal pitch of 1.6 µm on an ultra-precision lathe. The angle sensor is composed of two angle detection units based on the laser autocollimation method. A collimated laser beam with a diameter of 1 mm, which is output from a laser diode with a wavelength of 685 nm, is projected onto the linear scale grating. The positive and the negative first-order diffracted beams from the scale are received by the two angle detection units, respectively. The X-slide of the ultra-precision lathe is employed to generate the necessary scanning motion for the calibration. Based on the fact that the pitch deviations will cause changes in the positive and the negative first-order diffraction angles, which are equal in magnitude and opposite in sign, the pitch deviations can be obtained from the differential output of the angle sensor. The tilt error motion of the X-slide, which is a major error factor in on-machine calibration, can also be removed in the differential output. The robustness of the developed angle sensor for on-machine calibration has been confirmed by testing the basic performances of the sensor on the machine tool. The feasibility of the on-machine calibration result of pitch deviations has been verified through comparing with the off-machine calibration result.

Modelling of an Interconnected Power System using Solar-Wind Energy Integration

This paper revolves around the modification and improvement required for increasing the efficiency of the power generation and distribution system. As the demand for electricity and power consumption is increasing day by day, more efficient and capable system is required to reduce the burden and complicatedness of the power grid. The transformation or conversion of conventional power grid to smart grid which contains number of actuators, sensors and transducers which provides ability to control, analyse and maintain the grid which provides support for various types of new loads that are introducing in current period. Along with that, the involvement and guidance of the human element is also increasing rapidly in the power generation and distribution station. This involvement allows the monitoring, analysing, and recording the information to be done more precisely with less factors of error. Based on this, the simulation and integration of renewable energy sources simulated through MATLAB/Simulink reduces the burden on non-renewable source of energies such as Coal, Fuel, etc. Although it will be impossible to replace these sources completely but integrating such sources along with smart grid will allow to monitor and share information regarding the grid and its performance much efficiently. The data shared from smart grid plays a valuable role in estimation energy consumption and what may the demand in the future.

Influence of corneal curvature and peripheral thickness on tonometry readings

This study investigates the influence of peripheral corneal thickness (PCT) and its curvature on tonometry readings. The study included 49 patients (49 eyes) who were indicated for glaucoma surgery. Using bidirectional applanation tonometry, the following parameters were obtained: IOPcc, IOPg - intraocular pressure (IOP) corrected for corneal compensation, taken as the most reliable indicator; IOP converted to Goldmann measurement, taken as the result of applanation tonometry, ΔIOP (IOPcc-IOPg), CH and CRF (corneal hysteresis and corneal resistance factor). During corneal topography, the corneal thickness was studied in the center, PCT at 1.5; 2, 3, 4 and 5 mm from the center in four meridians, as well as ΔPCT (PCT 3 mm - PCT 1.5 mm), the curvature of the anterior and posterior surfaces of the cornea and the depth of the anterior chamber. Aberrometry was used to obtain refractometry data and the curvature of the anterior surface of the cornea. The influence of the studied parameters on ΔIOP was evaluated. ΔIOP correlated with CRF (r= -0.652), CH (r= -0.873), central corneal thickness (r= -0.293), PCT at all distances except 5 mm (r= -0.297; -0.287; -0.302; -0.303), with the strong and weak meridians of the anterior surface of the cornea (r=0.328; r=0.315), with the strong and weak meridians of the posterior surface, as well as the average curvature of the posterior surface (r=0.307; r=0.332; r=0.328). After step-by-step selection of the above parameters for creating a linear regression model for ΔIOP calculation, CH, CRF and PCT1.5mm remained in the model. The model describes ΔIOP with high accuracy (R2=0.974). Biomechanical parameters of the cornea are the leading factor of applanation tonometry error. Individual linear dimensions of the cornea (thickness, curvature) have a lesser effect.

NARRATIVE WRITING ABILITY PERFORMED BY STUDENTS OF ISLAMIC HIGH SCHOOL AL UKHUWAH SUKOHARJO: A SECOND LANGUAGE ACQUISITION CASE

<p class="Keyword">The research conducted at MA Al Ukhuwah Sukoharjo aimed to explore second language acquisition among high school students, specifically focusing on error types and factors influencing these errors with a gender-based analysis. Utilizing a descriptive qualitative approach and the four stages of analysis—domain, taxonomic, componential, and cultural theme—the study identified 841 errors, with misformation errors comprising the majority at 51.6%. Female students exhibited a higher error rate at 80.38% compared to their male counterparts (19.62%). Causes of errors, such as overgeneralization, incomplete rule application, incorrect hypothesis conception, and ignorance of rule restrictions, were identified, with the latter significantly impacting language mastery. These findings provide valuable insights for educators, informing strategies to address challenges in mastering English, particularly in areas like tense usage, sentence structure, diction, and conjunctions among high school students at MA Al Ukhuwah Sukoharjo.</p>

Information System Web-Based HSSE Performance In PT.XYZ

Information Technology systems are developing very quickly and are a challenge for all types of industries. Data management of a company is very important in this digital 4.0 era. This system aims to help computerized data and information management is expected to reduce the risk of human error factors. The method begins with analyzing needs using the discussion method, translating data into UML (Unified Modeling Language) diagrams and implementing systems using web-based applications by taking data at PT XYZ, Department of Health, Safety, Security, Environment in processing HSSE Performance data which still uses semi-conventional applications and redundancies, so that it will produce an Information System that can make it easier for Company Management to Monitor the Achievement of HSSE Department Performance Targets which are presented visually in the form of a Dashboard. The design of the information system uses a prototype method that can be added or reduced according to the development process that can be adjusted to the needs of the company. This web-based application designs an HSSE Performance Information System to support operational data management in the company. The information system to be designed is the HSSE Performance information system in the HSSE Department, providing information results that can be used by leaders and management in making decisions.

Increased Understanding Of Qibla Direction Through Hisab Training And Qibla Direction Determination Method

Abstract. The direction of Qibla is the direction of the place where Muslims go to worship; many still think that the direction is to the west. Therefore, it is unsurprising if there are still mosques, or mushala whose Qibla direction is not facing the Qibla, but to the west. The error factor in determining the direction of Qibla is the lack of human resources who understand the theory of Qibla direction, primarily normative and astronomical approaches. PCM Pleret, as a Muhammadiyah organization, has a role in enlightening its citizens, especially in matters of worship. This service aims to educate through training in measuring the direction of Qibla in theory and practice. The method used is in the form of lectures and discussions to strengthen theoretical aspects. In addition to lectures, partners will be taught to calculate and measure the direction of the Qibla of mosques and places used for prayer. The service results show that partners have increased in understanding and can accurately measure Qibla's direction.

Accelerated Degradation Reliability Modeling Based on Multiple Uncertainty Wiener Processes

Numerous scholars' studies usually adopt the Wiener process to establish industrial robot performance degradation models and randomize the drift coefficients to characterize the differences in individual degradation rates, but they do not take into account the influence of measurement errors on the accuracy of the models. Aiming at the above problems, combining the Wiener process and the accelerated degradation model, the accelerated degradation reliability model of industrial robots based on the multi-uncertainty Wiener process is established, and by adding the factor of measurement error, the model is able to more accurately characterize the influence of external factors on the degradation process of industrial robots. Bayesian theory, Markov chain Monte Carlo method and Bootstrap method are used to estimate the unknown parameters in the model. Finally, the accuracy of the proposed parameter estimation method and model is verified by simulating the industrial robot performance degradation data with Monte Carlo method.

SL-RI: Integration of supervised learning in robots for industry 5.0 automated application monitoring

Robotic technology holds a significant role within the realm of smart industries, wherein all functionalities are executed within real-time systems. The verification of robot operations is a crucial aspect in the context of Industry 5.0. To address this requirement, a distinctive design methodology known as SL-RI is proposed. This article aims to establish the significance of incorporating robots in the Industry 5.0 framework through analytical representations. In the context of this industrial monitoring system, the implementation of a supplementary algorithm is essential for effective management, as it enables the robots to acquire knowledge through the analysis and adaptation of restructured commands. The analytical model of robots is designed to accurately monitor the precise position and accelerations of robots, resulting in full-scale representations with minimal error conditions. The uniqueness of the proposed method in robotic monitoring system is related to the application process that is directly applied in Industry 5.0 by using various parametric cases where active movement of robots are monitored with rotational matrix representations. In this type of representations the significance relies in the way to understand the full movement of robots across various machines and its data handling characteristics that provides low loss and error factors.

Anterior Segment Changes and Refractive Outcomes after Cataract Surgery Combined with Gonioscopy-Assisted Transluminal Trabeculotomy in Open-Angle Glaucoma

To compare the accuracy of intraocular lens (IOL) calculation formulas in patients undergoing phacoemulsification combined with gonioscopy-assisted transluminal trabeculotomy (phaco-GATT) and to determine the predictive factors for refractive errors. Fifty-three eyes of 53 patients undergoing phaco-GATT were retrospectively reviewed. The preoperative and postoperative 3-month anterior segment (AS) parameters were measured by Scheimpflug camera. The mean prediction error (PE), mean absolute error (MAE) in the Sanders-Retzlaff-Kraft/theoretical (SRK/T), Barrett- Universal II, Hill-radial basis function (Hill-RBF) and Kane formulas were compared. The influence of biometric parameters on PE were analyzed by correlation analysis. Postoperatively, there was a statistically significant decrease in axial length (AL) and significant enlargement in anterior chamber depth (ACD), anterior chamber angle (ACA), and anterior chamber volume (p<0.001). The mean PE using SRK/T (-0.08 diopters [D]) was more myopic than in the Barret (0.01 D) and Hill-RBF (0.01 D). The PE closest to zero was in the Kane formula (0.001 D). The Kane formula provided a lower MAE (0.30±0.28 D) than the SRK/T (0.38±0.32 D) and Barrett (0.36±0.30 D) (p<0.001). The MAE in Hill-RBF (0.32±0.28) was comparable with that in Kane (p=0.02). Preoperative AL was significantly associated with PE in all formulas except Kane. Barrett was the only formula that did not have a significant correlation between PE and postoperative ACD and ACA. The Kane formula may provide higher predictability of the IOL power calculation than the SRK/T and Barrett-Universal II formulas in phaco-GATT surgery, which can cause significant changes in the AS and AL.

Comparative computational fluid dynamics analysis of fast pyrolysis of agricultural feedstocks across different biomass categories

This article presents a comprehensive Computational Fluid Dynamics (CFD) assessment of fast pyrolysis of three different agricultural feedstocks representing three different categories: Red oak (hardwood), Switchgrass (herbaceous biomass), and Picea glauca (softwood). The study aimed to evaluate the performance of each feedstock based on particle density, temperature distribution, and volume fraction distribution. The comparison of the simulation results with experimental data showed an average error factor below 13%. The study discovered that Red oak had the highest bio-oil production yield, followed by Switchgrass, which had a yield 10% lower, and Picea glauca, which had the weakest performance having a yield 20% lower than Red oak. Interestingly, optimal operating conditions for the production of bio-oil across all three feedstocks comprised a temperature of 500 °C and particle size of approximately 400 μm. However, increasing the pyrolysis temperature resulted in an increase in gas yield, whereas increasing particle size led to a rise in char production yield. Furthermore, the findings suggest that herbaceous biomass tends to perform better in fast pyrolysis for bio-oil production compared to softwood. This is attributed to the higher hemicellulose content in herbaceous feedstock which has a significant impact on bio-oil yield compared to cellulose and lignin. Moreover, hardwood and herbaceous samples, which have similar levels of cellulose and hemicellulose, demonstrated superior performance compared to softwood, which has lower hemicellulose content. Nonetheless, herbaceous biomass had about 10% extractable content, which made it perform weaker than hardwood.

Sustainability in High Reliability Organizations Employing Digitized Automation Inspection Processes

Digitization technologies offer several advantages over manual methods of accomplishing job-related tasks. Accurately measuring, documenting, and reporting surface damages, due to volume calculation variations are vital in increased efficiency, productivity, and thus mainly, human performance. Several sensation and perception issues were identified, mainly with concerns about accuracy of visual measurements that take place during quality control inspections. This research project portrays High Reliability Organizations utilizing digitized systems and automation concepts, with emphasis in Sensation, Perception, and Human Performance. Problem areas in measuring and assessing damaged Thermal Protection System (TPS) tile surfaces are identified and documented. Analysis of performance issues, causes, and effects, of human error factors are analyzed.

PERBAIKAN KUALITAS PRODUK MENGGUNAKAN METODE QUALITY CONTROL CIRCLE (QCC) DI PT. PUDAK ORIENTAL INDONESIA

PT. Pudak Oriental Indonesia is one of the companies that emphasize the importance of product quality. The common issue faced in the quality inspection process is the presence of numerous defective products that fail quality testing. The objective of this research is to identify the types of defects that frequently occur, identify their root causes, and reduce the defect rate using the Quality Control Circle (QCC) method, employing PDCA (Plan, Do, Check, Act), and Control Charts. QCC is a method aimed at reducing defects and improving product quality. The research findings indicate that the most frequent type of defect is white body defects, with a total of 309 pieces. The root cause analysis reveals that the most influential factors are human error and material factors. The results of the quality improvement implementation initially started at 18% and have reduced to 11%. Specifically for the white body defect type, after the defect mitigation efforts, the defect rate has been reduced from the initial 309 pieces to 54 pieces.