Data Processing Errors Research Articles

Automatic Observation of Astronomical Coordinates Using the Shandong University of Science and Technology/National Astronomical Observatories Digital Zenith Tube

Abstract The digital zenith tube (DZT) is developed based on the astrogeodetic and photogrammetric theory. One prototype of DZT integrating techniques of global positioning system (GPS) and charge-coupled device (CCD) photogrammetry has been developed jointly by Shandong University of Science and Technology and National Astronomical Observatories of Chinese Science Academy, China. It can automatically estimate astronomical coordinates in real time by CCD star image processing and GPS data processing. The DZT’s errors are analyzed in three aspects, namely, the instrument error, observation error, and data processing error. Reliability and accuracy of DZT integrating GPS and CCD are verified by the practical field operations. Observing results on many unknown points by the repeated observations of each point show the internal precision of the astronomical latitude and longitude. Observing results on several known points and the comparison with the EGM2008-derived results verify the external accuracy of the DZT, and the differences of these points in astronomical latitude and longitude are within ±0.15″ and greater than 1″, respectively.

Need for ‘Patent Search’ Modernisation and Potential for its Acceleration Leveraging AI/ML Models

Intellectual Property Rights (IPR) have played a crucial role in promoting innovations across the globe and of late the industry has seen a steep rise in innovation activity. There is an unprecedented urgency to help global IP offices in shortening the processing time, managing bureaucratic delays, and improving operational transparency. Patents are one of the most critical IP types among the 6 types where there is significant traction over the last couple of years. From ideation to the grant of the patent and its commercial use, the past patent data is required to be searched for and referred to for; 1] patentability assessment, 2] invalidity assessment, etc. Therefore, ‘Search’ becomes the most critical process across the patent lifecycle. Literature study indicates that issues involved in patent search (when traditional search techniques are employed) usually are around 1] data processing errors, 2] errors due to language pitfalls, 3] errors due to faulty syntax, and 4] classification errors. These erroneous searches result in a large number of false positives and false negatives. Artificial Intelligence (AI) and Machine Learning (ML) are leading the wave of technology development - both from a research and development perspective as well as their commercial use. Adopting these next-generation technologies presents great potential to help address the growing challenges in the patent search process. AI/ML based models are suitable predominantly for multi-lingual search, handling diverse data formats, image comparisons, and keyword matching. As IP databases across countries still lack standardization, advanced technologies such as generative AI are best suited to help accelerate the patent search process. Feasibility assessment of leveraging various AI/ML models to address efficiency and effectiveness issues of patent search can be performed through a 3-part framework (3i) focussing on various dimensions such as Integrate, Infer, and Intelligence. AI/ML model applicability can be assessed against specific objectives of each part viz. 1. Integrate – integration with various patent databases, 2. Infer – data extraction and transformation into a standardized data set suitable for comparative analysis and 3. Intelligence – comparison, matching, and decision-making for search objectives. At a global scale, further deliberations and studies on this subject are of immense value in the areas of knowledge and policy-making thereby benefiting practitioners, the academic fraternity, and society

Calibration of Transition-edge Sensor (TES) Bolometer Arrays with Application to CLASS

The current and future cosmic microwave background (CMB) experiments fielding kilopixel arrays of transition-edge sensor (TES) bolometers require accurate and robust gain calibration methods. We simplify and refactor the standard TES model to directly relate the detector responsivity calibration and optical time constant to the measured TES current I and the applied bias current I b. The calibration method developed for the Cosmology Large Angular Scale Surveyor (CLASS) TES bolometer arrays relies on current versus voltage (I–V) measurements acquired daily prior to CMB observations. By binning Q-band (40 GHz) I–V measurements by optical loading, we find that the gain calibration median standard error within a bin is 0.3%. We test the accuracy of this I–V bin detector calibration method by using the Moon as a photometric standard. The ratio of measured Moon amplitudes between the detector pairs sharing the same feedhorn indicates a TES calibration error of 0.5%. We also find that, for the CLASS Q-band TES array, calibrating the response of individual detectors based solely on the applied TES bias current accurately corrects TES gain variations across time but introduces a bias in the TES calibration from data counts to power units. Since the TES current bias value is set and recorded before every observation, this calibration method can always be applied to the raw TES data and is not subject to I–V data quality or processing errors.

Thresholding Methods for Reduction in Data Processing Errors in the Laser-Textured Surface Topography Measurements.

There are many factors influencing the accuracy of surface topography measurement results: one of them is the vibrations caused by the high-frequency noise occurrence. It is extremely difficult to extract results defined as noise from the real measured data, especially the application of various methods requiring skilled users and, additionally, the improper use of software may cause errors in the data processing. Accordingly, various thresholding methods for the minimization of errors in the raw surface topography data processing were proposed and compared with commonly used (available in the commercial software) techniques. Applied procedures were used for the minimization of errors in the surface topography parameters (from ISO 25178 standard) calculation after the removal and reduction, respectively, of the high-frequency noise (S-filter). Methods were applied for analysis of the laser-textured surfaces with a comparison of many regular methods, proposed previously in the commercial measuring equipment. It was found that the application of commonly used algorithms can be suitable for the processing of the measured data when selected procedures are provided. Moreover, errors in both the measurement process and the data processing can be reduced when thresholding methods support regular algorithms and procedures. From applied, commonly used methods (regular Gaussian regression filter, robust Gaussian regression filter, spline filter and fast Fourier transform filter), the most encouraging results were obtained for high-frequency noise reduction in laser-textured details when the fast Fourier transform filter was supported by a thresholding approach.

Force inference in granular materials: Uncertainty analysis and application to three-dimensional experiment design.

Interparticle forces are known to influence mechanical and physical properties of granular materials. A method for inferring forces in two-dimensional and three-dimensional experiments has recently been developed and applied to the problem of examining force statistics, energy dissipation, fracture mechanics, and force-property relations. However, a systematic analysis of uncertainties in the forces inferred through this method has not been undertaken. In this paper, our goal is therefore to perform such a systematic analysis. We first review and modify the force inference technique to eliminate its sensitivity to the choice of units and coordinate system origin. We then use discrete-element method simulations to perform a systematic study of how experimental uncertainties and data-processing errors lead to errors in inferred forces. For the considered experiments and simulations, we find that (1) errors in inferred force magnitudes and orientations increase as the ratio between particle stress uncertainties and a measure of stress imposed on the system increases, but remain small in the largest forces in a material; (2) the absence of a moderate number of particle stress tensors in the force inference procedure leads to negligible errors in inferred force magnitudes and orientations; and (3) particle stress tensors that cannot be directly measured during experiments can be "recovered" through the force inference procedure. Based on our results, we make recommendations for future experiment design to reduce uncertainties in inferred forces.

An intelligent leakage detection method for diaphragm wall joints based on fiber Bragg grating sensors and intelligent algorithms

The leakage detection method based on fiber Bragg grating (FBG) sensing technology is an effective method to determine leakage points in diaphragm wall joints. However, the detection method involves cumbersome data processing which causes manual data processing errors and costs time. In this work, an intelligent leakage detection method for diaphragm wall joints based on FBG sensing signals was proposed. Firstly, a field study of the leakage detection method was carried out in a new urban expressway in Hohhot, Inner Mongolia, China. The field monitoring data were compared with test data, and characteristics of the FBG wavelength curve and mechanism of leakage detection were analyzed. In addition, four intelligent detection models including a convolutional neural network, support vector machine (SVM), decision tree, and random forest were established. Results showed that the proposed method is effective and efficient in identifying and locating leakage through diaphragm walls.

Anthropometric Equations to Determine Maximum Height in Adults ≥ 60 Years: A Systematic Review.

Although it is common to measure bone lengths for study, methodological errors in data measurement and processing often invalidate their clinical and scientific usefulness. This manuscript reviews the validity of several published equations used to determine the maximum height in older adults, since height is an anthropometric parameter widely employed in health sciences. A systematic review of original articles published in the English, Spanish, or Portuguese languages was performed in PubMed, ScienceDirect, EBSCO, Springer Link, and two institutional publisher integrators (UACJ and CONRICYT). The search terms were included in the metasearch engines in a combined way and text form using the Boolean connectors AND and OR {(Determination OR Estimation OR Equation) AND Height AND (Elderly OR “Older adults”)}. Eleven manuscripts were selected from 1935 records identified through database searching after applying the following criteria: (1) original articles that designed and validated equations for the determination of height by anthropometric methods in adults 60 years of age and older and (2) manuscripts that presented robust evidence of validation of the proposed regression models. The validity of the reported linear regression models was assessed throughout a manuscript review process called multi-objective optimization that considered the collection of the models, the prediction errors, and the adjustment values (i.e., R2, standard error of estimation, and pure error). A total of 64 equations were designed and validated in 45,449 participants (57.1% women) from four continents: America (85.3%, with 46 equations), Asia (8.1%, with 10), Europe (4.6%, with 7), and Africa (2.0%, with 1); the Hispanic American ethnic group was the most numerous in participants and equations (69.0%, with 28). Due to various omissions and methodological errors, this study did not find any valid and reliable equations to assess the maximum height in older adults by anthropometric methods. It is proposed to adjust allometric mathematical models that can be interpreted in the light of ontogenetic processes.

The Importance of Accurate Timing on Land Seismic Data

Although the requirement for accurate timing of both the sources and receivers used for land seismic data acquisition has long been known, the numerical requirement for, and impact of, timing accuracy on data quality is poorly defined. In this paper we derive a method for determining the theoretical timing requirement for data acquisition. We then demonstrate the impact of poorly timed data on data quality and examine our ability to remove timing errors in data processing. Source timing variations can be corrected through the application of surface-consistent static correction but only if multiple shots have not been stacked during acquisition. Receiver timing variations are more problematic and the ability to correct for them relies on a sufficiently dense acquisition geometry.

Optimized Umkehr profile algorithm for ozone trend analyses

Abstract. The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations – Boulder, the Haute-Provence Observatory (OHP), the Mauna Loa Observatory (MLO), Lauder – against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined solar backscatter ultraviolet (SBUV) and Ozone Mapping and Profiler Suite (OMPS) records (NASA aggregated and NOAA cohesive datasets). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 h). Umkehr Averaging kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) Global Modeling Initiative (M2GMI) and NASA Global Modeling Initiative chemistry transport model (GMI CTM) ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.

Atomic Force Microscopy Nanoindentation Method on Collagen Fibrils.

Atomic Force Microscopy nanoindentation method is a powerful technique that can be used for the nano-mechanical characterization of bio-samples. Significant scientific efforts have been performed during the last two decades to accurately determine the Young’s modulus of collagen fibrils at the nanoscale, as it has been proven that mechanical alterations of collagen are related to various pathological conditions. Different contact mechanics models have been proposed for processing the force–indentation data based on assumptions regarding the shape of the indenter and collagen fibrils and on the elastic or elastic–plastic contact assumption. However, the results reported in the literature do not always agree; for example, the Young’s modulus values for dry collagen fibrils expand from 0.9 to 11.5 GPa. The most significant parameters for the broad range of values are related to the heterogeneous structure of the fibrils, the water content within the fibrils, the data processing errors, and the uncertainties in the calibration of the probe. An extensive discussion regarding the models arising from contact mechanics and the results provided in the literature is presented, while new approaches with respect to future research are proposed.

Development Rime Syar'i Business & Administration Management System with Rapid Application Development Method

This research aims to produce an administrative information system design to increase accuracy in data processing and the ability to provide faster information for a business and increase the accuracy of service to consumers. This study also aims to identify information system problems on the system running on Rime Syar'i business and produce a Web-based administrative information application program that includes administrative transactions to produce transaction reports and reports that are needed to facilitate business management. Rime Syar'i. The conclusion obtained from this research is that using a web-based information system, can minimize errors in data processing, increase the effectiveness and efficiency of Rime Syar'i's business work in a better direction, and ease in making reports.

Physics-Based Guidelines for Accepting Reasonable Dynamic Simulations of Movement.

During dynamic simulations, residuals are nonphysical generalized forces/moments that dynamically balance external and inertial forces/moments, accounting for data processing and modelling errors. Hicks et al. (2015) made the original residual threshold recommendations for an acceptable simulation, but these thresholds are not based on the dynamic, physics-based movement characteristics. In this study, we present three new, physics-based guidelines for accepting dynamic simulations of movement using zero moment point computations and thresholds for forces, center of pressure, and free moment. We formulate new guidelines and evaluate them alongside the original 2015 recommendations using two movements: single-leg jump-landing (SLJL) and walking gait. We also present a MATLAB function for users to test if their simulations meet these guidelines. We found that on average, only 4.3% (SLJL) and 8.2% (walking gait) of the original 2015 residuals volume met all the new physics-based guidelines. The free-moment guideline was the most restrictive for reasonable simulations, especially for high-velocity movements at times with lower vertical ground reaction forces. Additionally, some of the new recommended residuals volume fell outside of the original 2015 recommendations. Moreover, accepting reasonable simulations using different thresholds leads to different joint torques as high as 24 Nm (SLJL) and 8.2 Nm (walking gait). The physics-based guidelines are overall more restrictive than the original 2015 recommendations and elicit different simulation kinetics. Using different guidelines may lead to different conclusions and clinical interpretations. We advocate for the physics-based guidelines as they are built upon the dynamic, physics-based characteristics of the movement.

Design and Development of Software Project Management System using Scrum

Good project management is a crucial factor for the smooth implementation of projects in an application development organization. Management activities carried out manually have the potential to result in errors in data processing, and it is difficult to monitor project progress, which often results in time and financial losses. This research was conducted to overcome this problem by building a project management system based on the Scrum method using the Laravel framework and applying a multiple linear regression algorithm in estimating time for each project activity with parameters of the number of people involved and the type of work, as well as competency mapping on the recommendations in the human resource allocations. The Scrum method is used because of its flexibility and fast adaptability to the system development process. The result of this research is a software development project management system that helps organizations in allocating human resources and time management. The resulting multiple linear regression model obtains a Mean Absolute Error (MAE) of 349.97. Descriptive analysis conducted on user responses stated that user responses were positive towards the use of the project management system.

The reliability of measuring medial gastrocnemius muscle-tendon unit lengths during gait.

Ultrasound imaging combined with 3D motion analysis allows for in-vivo assessment of muscle-tendon unit lengths during gait. The clinical relevance of analysing the medial gastrocnemius (MG) and Achilles muscle-tendon junction (MTJ), MG mid-muscle belly fascicles (FAS) and muscle thickness was shown. However, their reliability error estimations over the gait cycle is unknown. What are the intra- and inter-session errors associated with extracting MG belly, thickness, FAS and tendon lengths using ultrasound during gait in healthy participants? 3D gait analysis was carried out in ten healthy adults as they walked on an instrumented treadmill at a comfortable walking speed. An ultrasound probe was secured on the leg and tracked by 3D motion analysis. Images were collected during two walking trials with the probe on the MG muscle-belly to estimate FAS lengths and muscle thickness, and during two trials with the probe on the MTJ to estimate muscle-belly and tendon lengths. A second session was performed after 5 ± 4 days where a different operator placed the ultrasound probe. The standard deviation (SD) of absolute and relative lengths changes during the gait cycle over different trials were calculated per participant. SD values averaged over participants represented intra- and inter-session errors. For all assessed variables, the intra-session errors were <2.2 mm, except for the FAS lengths (3.1 mm). The inter-session errors were larger than the intra-session, with the highest values found for the absolute muscle-tendon unit lengths (5.6 mm). Relative length errors were smaller than absolute length errors. Intra-session errors, which may reflect natural variability and data processing errors, seem more critical when extracting absolute FAS than muscle-tendon lengths. Standardized probe positioning on the MTJ between sessions may improve the inter-session reliability. Expressing the lengths relative to their lengths as the beginning of the gait cycle reduces the inter-session errors.

Aplikasi Akuntansi Simpanan Anggota Pada KUD Bangkit Abadi Desa Bandorasawetan

The Bangkit Abadi Village Unit Cooperative (KUD) is a cooperative located in Bandorasawetan Village, whose main activity is providing savings services for cooperative members with the aim of prospering cooperative members and the surrounding community. With the existence of this cooperative, it is hoped that it will create a desire and increase public awareness to save. This KUD does not yet have a good computerized system. Therefore, there are still some obstacles in KUD Bangkit Abadi in terms of new member registration activities and member savings. These activities will run smoothly if supported by a good system and by implementing a good internal control system in cooperatives, so as to prevent errors in data processing. The procedures that apply to the KUD include related parts, namely registration, member data, internal control systems, and documents used. The analysis and design stages of the application system are described using flowcharts, Data Flow Diagrams (DFD), Entity Relationship Diagrams (ER-Diagrams) and developed using MySQL database as a programming language. This relationship is narrated into several diagrams, namely: context diagrams, data flow diagrams level 0 and level 1, relationships between entities, and relationships between tables used. The results obtained from the design of this application are in the form of member book reports, savings data reports, and general journal reports as a form of description of the activities of new member registration and member savings at the Bangkit Abadi Village Cooperative Unit.Key words: Applications, Accounting, Savings, Cooperatives

Processing and Validation of FORMOSAT‐7/COSMIC‐2 GPS Total Electron Content Observations

AbstractSlant absolute total electron content (TEC) is observed by the Formosa Satellite‐7/Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (FORMOSAT‐7/COSMIC‐2, F7/C2) Tri‐GNSS Radio Occultation System (TGRS) instrument. We present details of the data processing algorithms, validation, and error assessment for the F7/C2 global positioning system (GPS) absolute TEC observations. The data processing includes estimation and application of solar panel dependent pseudorange multipath maps, phase to pseudorange leveling, and estimation of separate L1C‐L2C and L1C‐L2P receiver differential code biases. We additionally perform a validation of the F7/C2 GPS absolute TEC observations through comparison with colocated, independent, TEC observations from the Swarm‐B satellite. Based on this comparison, we conclude that the accuracy of the F7/C2 GPS absolute TEC observations is less than 3.0 TEC units. Results are also presented that illustrate the suitability of the F7/C2 GPS absolute TEC observations for studying the climatology and variability of the topside ionosphere and plasmasphere (i.e., altitudes above the F7/C2 orbit of 550 km). These results demonstrate that F7/C2 provides high quality GPS absolute TEC observations that can be used for ionosphere‐thermosphere data assimilation as well as scientific studies of the topside ionosphere and plasmasphere.

Seasonal and long-term vertical land motion in Southwest China determined using GPS, GRACE, and surface loading model

Owing to the intense tectonic activity and significant seasonal surface mass change, Southwest China is characterized by noticeable vertical land movement. We determined the vertical movement of Southwest China using 10 years of data from 41 continuous global positioning system (GPS) stations, gravity recovery and climate experiment (GRACE), and surface loading model (SLM). The annual variation in hydrological loading is the main factor causing the seasonal oscillation of surface deformation in Southwest China. Seasonal deformations captured by GPS, GRACE, and SLM are consistent to a certain extent, and the correlation coefficients between GPS/GRACE, and GPS/SLM are 0.82 and 0.81, respectively. After deducting the results yielded by GRACE and SLM from the GPS time series, the average reductions in root mean square were 41.3% and 38.0%, respectively. However, some systematic differences were observed among the annual amplitudes and phases of the seasonal deformations among the three products. For example, the average amplitudes estimated by GRACE and SLM were 7.4 mm and 6.1 mm, respectively, which were smaller than the amplitude deduced from GPS (9.7 mm). Furthermore, mean phase delays of 16, 22, and 6 days were observed between GPS/GRACE, GPS/SLM, and GRACE/SLM. The data processing errors and local geophysical signals in GPS and the underestimation of land water storage in GRACE and SLM were jointly responsible for the systemic differences. The simulated data show that the misestimating of hydrological loading can explain approximately 50%, 64%, and 83% of the phase delays between GPS/GRACE, GPS/SLM, and GRACE/SLM, respectively. In addition, we obtained long-term vertical crustal motion rates by subtracting the loading deformation rates estimated by GRACE from the linear rates of the GPS. The vertical crustal motion in this region is block-dependent. The Central Yunnan block and its eastern boundary are uplifted; meanwhile, the Southwest Yunnan block, which features stretching in the horizontal direction, appears to be subsiding. The aforementioned results can provide data support for the study of water resource utilization and geodynamics in Southwest China.

Comparison of Moora, Waspas and SAW Methods in Decision Support Systems

Education is a process in the framework that can adapt to the environment and thus will cause changes in themselves that enable it to involve all that is in society. In this case, the process of selecting the best teachers and staff in data processing is still done manually by conducting tests through several criteria that have been made. Criteria used for the process. There are 19 criteria. The selection process carried out manually has several weaknesses so that it will result in errors in data processing. For this reason, a Decision Support System is needed that can be used in the process of selecting the best Teachers and Staff. In this study, using the calculation method calculation methods Moora, SAW, and WASPAS with scholarship recipients. The results obtained from the Moora Method are 3 (three) highest values at V1 = 1.89; V8 = 1.81; and V2 = 1.80, the SAW Method was 3 (three) highest values at V1 = 10.38; V8 = 9.90; and V2 = 9.87. The WASPAS method that 3 is highest at V1 = 5.07; V8 = 4.72; and V2 = 4.68. The system created using the SAW method because it provides the Best Alternative value and provides the best ranking results

Experimental Investigation of Wing Accuracy Quantification using Point Cloud and Surface Deviation

A rapidly advancing lean production industry demands quick manufacturing solutions with greater precision and accuracy. This paper proposes a framework for the accurate quantification of a die-casted wing using laser scanning and reverse engineering technique. In this technique, the wing upper and lower surfaces are scanned using a Coordinate Measuring Machine (CMM). This scanned data is then imported into CAD software to generate the surface using Free Form Reverse Engineering (FFRE). The model fitness test patronizes the curve fitting used for the surface generation. The generated surface and the original 3D CAD model are investigated using deviation analysis for inaccuracies originating due to manufacturing and data acquisition. The wing is further analyzed by the point data to 3D CAD model deviation analysis. The methodology adopted significantly minimizes the data acquisition and data processing error allowing deviation to be solely traced back to the manufacturing technique.

IDENTIFICATION AND PROCESSING OF DATA ANOMALIES IN MACHINE LEARNING TASKS

The paper presents the procedure of identification and processing of data anomalies at the stage of preliminary data processing in machine learning tasks. The procedure consists of three stages. At the first stage, emissions are detected in the data samples. A large number of methods are used for this. The choice of a particular method depends on the task of machine learning, the structure of the data set and the types of data being processed. The methods used at this stage are methods of statistical tests, methods of metric tests, methods of model tests, iterative methods, methods of machine learning, ensemble methods. Until the second stage, the analysis of the causes of emissions is carried out. The causes of emissions include: causes of measurement errors and causes of data processing errors, the results of external influences, or errors in data records. In the third stage, there is a final processing of data sets with emissions, in which there is a removal of emissions or normalizing transformations. The effectiveness of the procedure was tested on different data sets.