An innovative method of fault detection in power transformers

The Bayesian classifier is a priori the optimal solution for minimizing the total error in problems of statistical pattern recognition. The article suggests using the classifier as a regular tool to increase the reliability of defect recognition in power oil-filled transformers based on the results of the analysis of gases dissolved in oil. The wide application of the Bayesian method for solving tasks of technical diagnostics of electrical equipment is limited by the problem of the multidimensional distribution of random parameters (features) and the nonlinearity of classification. The application of a generalized feature of a defect in the form of a nonlinear function of the transformer state parameters is proposed. This simultaneously reduces the dimension of the initial space of the controlled parameters and significantly improves the stochastic properties of the random distribution of the generalized feature. A special algorithm has been developed to perform statistical calculations and the procedure for recognizing the current technical condition of the transformer using the generated decision rule. The presented research results illustrate the possibility of the practical application of the developed method in the conditions of real operation of power transformers.

Non-Global Privacy Protection Facing Sensitive Areas in Face Images

Face images, as an information carrier, are naturally weak in privacy. If they are collected and analyzed by malicious third parties, personal privacy will leak, and many other unmeasurable losses will occur. Differential privacy protection of face images is mainly being studied under non-interactive frameworks. However, the ε-effect impacts the entire image under these frameworks. Besides, the noise influence is uniform across the protected image, during the realization of the Laplace mechanism. The differential privacy of face images under interactive mechanisms can protect the privacy of different areas to different degrees, but the total error is still constrained by the image size. To solve the problem, this paper proposes a non-global privacy protection method for sensitive areas in face images, known as differential privacy of landmark positioning (DPLP). The proposed algorithm is realized as follows: Firstly, the active shape model (ASM) algorithm was adopted to position the area of each face landmark. If the landmark overlaps a subgraph of the original image, then the subgraph would be taken as a sensitive area. Then, the sensitive area was treated as the seed for regional growth, following the fusion similarity measurement mechanism (FSMM). In our method, the privacy budget is only allocated to the seed; whether any other insensitive area would be protected depends on whether the area exists in a growing region. In addition, when a subgraph meets the criterion for merging with multiple seeds, the most reasonable seed to be merged would be selected by the exponential mechanism. Experimental results show that the DPLP algorithm satisfies ε-differential privacy, its total error does not change with image size, and the noisy image remains highly available.

Alkaline phosphatase interference in immuno-enzymatic assays.

Background: Alkaline phosphatase (ALP) enzymes are widely used as signal amplifiers in immunoenzymatic methods. Conditions that cause ALP elevations, such as bone or liver diseases can cause interference in immunoenzymatic methods. Objective: We aimed to examine ALP's effect on immunoenzymatic assay by adding isolated pure ALP to the prepared serum pool. Material and Methods: We prepared a serum pool and divided into 4 groups. By adding isolated pure ALP at different concentrations to each group, we obtained sample groups containing ALP enzyme at concentrations of 85 U/L, 340 U/L, 870 U/L and 1570 U/L. In each group, 20-repetition of βhCG, Ferritin, FT4, TSH, Troponin I and Vit B12 tests were performed. Coefficient of variation, bias, and total error were calculated. All groups were compared by using Friedman test for paired samples. Result: After ALP addition, the calculated total error values of FT4, βhCG and troponin I tests were found to be above the acceptable error limits. There were statistically significant differences in βhCG ,FT4, troponin I and Vit B12 tests when compared to the baseline ALP level (P<0,0125).Conclusion: Isolated ALP elevations can be a source of interference for immunoenzymatic methods.KeywordsAlkaline phosphatase, ALP, bias, immunoenzymatic, total error

Development of Detection and Volumetric Methods for the Triceps of the Lower Leg Using Magnetic Resonance Images with Deep Learning

Purpose: A deep learning technique was used to analyze the triceps surae muscle. The devised interpolation method was used to determine muscle’s volume and verify the usefulness of the method. Materials and Methods: Thirty-eight T1-weighted cross-sectional magnetic resonance images of the triceps of the lower leg were divided into three classes, i.e., gastrocnemius lateralis (GL), gastrocnemius medialis (GM), and soleus (SOL), and the regions of interest (ROIs) were manually defined. The supervised images were classified as per each patient. A total of 1199 images were prepared. Six different datasets separated patient-wise were prepared for K-fold cross-validation. A network model of the DeepLabv3+ was used for training. The images generated by the created model were divided as per each patient and classified into each muscle types. The model performance and the interpolation method were evaluated by calculating the Dice similarity coefficient (DSC) and error rates of the volume of the predicted and interpolated images, respectively. Results: The mean DSCs for the predicted images were >0.81 for GM and SOL and 0.71 for GL. The mean error rates for volume were approximately 11% for GL, SOL, and total error and 23% for GL. DSCs in the interpolated images were >0.8 for all muscles. The mean error rates of volume were <10% for GL, SOL, and total error and 18% for GM. There was no significant difference between the volumes obtained from the supervised images and interpolated images. Conclusions: Using the semantic segmentation of the deep learning technique, the triceps were detected with high accuracy and the interpolation method used in this study to find the volume was useful.

Effectiveness of an Assistive Instrument for Physical Therapists with Visual Impairment to Conduct the Muscle Tightness Test

Disability sports have been globally promoted to achieve an inclusive society. However, the current opportunities for people with disabilities are few in terms of participating in supporting positions, such as athletic trainers. In Japan, many people with visual impairment (VI) work as physical therapists; thus, they can become active as medical staff in the sports field. An example of a medical assessment is the muscle tightness test (MTT); however, conducting it is expected to be difficult for people with VI. To improve this difficulty, the current study developed an assistive instrument (AsI) and examined its effectiveness. We recruited 22 physical therapists with VI. The measurement for MTT targeted the hamstrings, iliopsoas, gastrocnemius, and quadriceps. The participants performed the MTT using a universal goniometer (UG) and the AsI and filled up a questionnaire. AsI was compared against UG based on three aspects, namely, ease, accuracy, and measurement time. In terms of ease, significant differences were observed in 9 out of 12 questionnaire items. The mean (SD) score for “Comprehensive ease of the MTT” improved from 2.8 (1.0) to 3.9 (0.8). For accuracy, the AsI yielded a decrease in the total error of the measurement. Lastly, the measurement time for AsI was longer than that for the UG. Therefore, the AsI was effective in terms of ease and accuracy, whereas measurement time remained as an issue.

Error analysis of the cutting machine step adjustable drive

The implementation precision of a number of adjustment bodies of a metal-cutting machine is also the most important indicator of its quality, a strictly standardized industry standard, technical conditions for manufacturing and acceptance. Moreover, the standard for limiting the error is set depending on the used denominator of the series. An essential feature of the precision of the series being implemented is that it is determined not by an error in parts’ manufacturing, but by the disadvantages of the used method of kinematic calculation. The established modes largely determine the efficiency of processing on metal-cutting machines. If the setting is set to an underestimated mode, then the performance is reduced accordingly. In the case of the mode overestimation, this leads to a decrease in durability and losses due to increased regrinding and tool changes. Creation of a complex of mathematical models for the design kinematic calculation of the metal-cutting machines’ main movement drive, which allows reducing the error in the implementation of a series of preferred numbers and increasing machining precision. The article provides a mathematical complex for analyzing the total error components, which allows determining and evaluating the total error of the drive of a metal-cutting machine by analyzing its constituent values with high precision: errors of a permanent part, errors of a multiplier part, rounding errors of standard numbers, errors in the electric motor and belt transmission. The presented complex helps to identify the role of the rounding error of preferred numbers in the total relative error formation and makes it possible to reduce it, which allows solving the problem of increasing the step adjustable drive precision. When using a mathematical complex, a fundamentally new opportunity for creating a scientific base appears, developing algorithms and programs for engineering calculation of tables that facilitate the selection of the numbers of teeth for multiple groups, structures and guaranteeing high precision of the implemented series.

Development of an In-House Rapid Antimicrobial Susceptibility Testing Protocol for Positive Blood Culture and Its Implementation in Routine Microbiology Laboratories

Bloodstream infections (BSI) are associated with high morbidity and mortality and remain a leading cause of death. Blood culture (BC) including the identification and the antimicrobial susceptibility testing of the causative microorganisms should be performed as soon as possible. In this study, we developed an in-house rapid antimicrobial susceptibility testing (rAST) protocol for positive BC. First, the rAST was performed in the simulated positive BC of standard strains (Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 25923, and Pseudomonas aeruginosa ATCC 27853) at three different times to assess the reproducibility and operability by dispensing four drops of BC broth onto a Mueller–Hinton agar plate after a positive signal. Furthermore, the rAST was performed in clinical positive BCs. The results of rAST at 4, 6, 8, and 18 h of incubation were compared with results of the standard 16- to 20-h disk diffusion method, and the preliminary breakpoints of the rAST method were established according to the inhibition diameter of sensitive strains and resistant strains. Finally, the rAST was performed in the simulated positive BC of clinical strains to evaluate the availability of the preliminary breakpoints. The rAST results of standard strains were distributed evenly at three different times. Among the 202 clinical strains used to establish the preliminary breakpoints, the number of zone diameters that could be read and interpreted (60, 87, 98, and 100%) increased with incubation time (4, 6, 8, and 18 h), and the categorical agreement was acceptable, with total error rates of 3.0, 2.3, 2.1, and 1.3% at 4, 6, 8, and 18 h of incubation, respectively. In conclusion, the in-house rAST protocol for positive BC can be implemented in routine laboratories. It provides reliable antimicrobial susceptibility testing results for BSI pathogens after 4–6 h of incubation.

Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up

One of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence on the quality of the photogrammetric study of a 3D urban mock-up. An important issue in this study was the measurement and evaluation of the artificial light sources used, based on illuminance (E), correlated colour temperature (CCT), colour rendering index (CRI) and Spectral power distribution (SPD) and the evaluation of the obtained point clouds (seven photogrammetric products of the same object, developed for seven different lighting conditions). The general values of the quality of the photogrammetric studies were compared. Additionally, we determined seventeen features concerning the group of tie-points in the vicinity of each F-point and the type of study. The acquired traits were related to the number of tie-points in the vicinity, their luminosities and spectral characteristics for each of the colours (red, green, blue). The dependencies between the identified features and the obtained XYZ total error were verified, and the possibility of detecting F-points depending on their luminosity was also analysed. The obtained results can be important in the process of developing a photogrammetric method of urban lighting monitoring or in selecting additional lighting for objects that are the subject of a short-range photogrammetric study.

Strategy to Decrease the Angle Measurement Error Introduced by the Use of Circular Grating in Dynamic Torque Calibration

A circular grating angle encoder is a key component in the dynamic torque calibration system. To improve the accuracy of an angle measurement, in this paper, the source of the angle measurement error of the circular grating is analyzed; an eccentricity error model and an inclination error model are proposed, respectively; further, these two models are combined to establish a total error model. Through the simulation study with the models, the conditions, in which the eccentricity error or inclination error can be ignored, are discussed. The calibration and compensation methods of the angle measurement error are given, and a progressive error compensation function which integrates the first harmonic fitting and the second harmonic fitting is obtained. An experiment is performed to verify the proposed calibration and compensation methods. The peak-to-peak value of the compensated angle measurement error of the single reading head can be reduced by about 93.76%, which approximates to the error of the mean value of the double reading heads. The experimental results show that the error calibration and compensation method based on the proposed error model can effectively compensate the angle measurement error of the circular grating with a single reading head, and obtain a high-precision measurement angle.