Error Level Research Articles

ОБОСНОВАНИЕ ПАРАМЕТРОВ МАРКШЕЙДЕРСКОЙ СЪЕМКИ СКЛАДОВ ПОЛЕЗНОГО ИСКОПАЕМОГО ПРИ ПОМОЩИ БПЛА

Determination of mineral residuals in stockpiles based on the results of surveying is an important task of the surveying service at any mining enterprise. Currently, the aerial photogrammetric method of surveying using UAVs is widely used for surveying because of its relative availability, efficiency and safety of work. The result of the survey is a digital terrain model containing millions of coordinated points. At the same time, the volume of the warehouse should be established taking into account the required value of the error of its determination. The main factors influencing the value of the volume determination error are identified, the classification of aerial survey methods is proposed. The results of researches on the influence of the revealed factors on the error value of volume calculation are presented. Recommendations are given for surveying and calculating the volumes of warehouses, providing the required level of volume determination error.

Study and application of joint assessment model for construction risk of Xiangxi Yangtze River Bridge

Closure of main arch rib is the key process of steel box girder arch bridge construction. The way to achieve quantitative and accurate prediction of closure error risk remains to be studied in depth. Taking the construction risk model of closure of main arch rib of Xiangxi Yangtze River Bridge as an example, firstly, the causal relationship between prior data and closure error of main arch rib is considered to construct Bayesian network topology; Further, the central limit theorem (CLT) is used to update the prior distribution of the parent nodes in the network using dynamic multi-source monitoring data; Then the finite element analysis and BP neural network are combined to reproduce the corresponding relationship between the arch rib closure error and the influencing factors. Finally, the probability distribution is determined by the Monte Carlo method, and the quantitative prediction of the joint construction risk error is realized. The analysis data shows that the risk probability of arch rib vertical error of Xiangxi Yangtze River Bridge is transmissible, and the risk level of arch rib closure error reaches Grade IV when it is 75∼125mm. Therefore, the prestress of anchor cable, tower buckle offset and local temperature should be closely monitored during construction. The calculated value of the joint prediction model of construction risk is consistent with the actual closure control error trend of the project, which can provide reference for the prediction and regulation of related bridge construction risks.

ШЛЯХИ ЗМЕНШЕННЯ ПОХИБОК ВИМІРЮВАННЯ ДІЕЛЕКТРИЧНОЇ ПРОНИКНОСТІ СЛАБОПОГЛИНАЮЧИХ ДІЕЛЕКТРИКІВ У МІЛІМЕТРОВОМУ ТА СУБМІЛІМЕТРОВОМУ (ТЕРАГЕРЦОВОМУ) ДІАПАЗОНАХ ДОВЖИН ХВИЛЬ МЕТОДОМ ПОВЕРХНЕВОГО ПЛАЗМОННОГО РЕЗОНАНСУ

Subject and Purpose. The sources of errors are identified that may arise in the course of terahertz-range measurements of the dielec- tric constant of weakly absorbent dielectrics, if performed within the surface plasmon resonance (SPR) technique. Possible ways are analyzed for reducing or fully eliminating such errors. Methods and Methodology. Specific details of applying the SPR method for dielectric constant measurements have been analyzed, with the aim of identifying the major factors that particularly affect the measurement accuracy. Results. It has been noted that in order to reduce the level of backlight interference (which may lead to blinding the receiver), it is expedient to make surface resonance records via frequency scanning. In that case the impact of the interference signal nonstationa- rity arising from the partial conversion of the surface wave energy into that of the volume wave, which occurs at the grating edges, is markedly lower than in the case of angular scanning. A mathematical expression has been derived which suggests a relation between scanning step sizes in angle and in frequency (for the angular and frequency scanning, respectively). As has been shown, a better mea- surement accuracy is achievable if the SPR is recorded as a function of frequency. Indeed, the frequency can be varied, with the use of familiar technologies, in steps of a much smaller size than such adopted for angular scanning. Errors in the above measurements can also arise if the resonance is excited on a grating whose Fourier spectrum contains many high-frequency components which carry a noticeable portion of the diffracted radiation energy. These energy losses can be greatly reduced if the SPR is excited on a grating whose profile involves the lowest number of spatial Fourier harmonics. Conclusions. The method suggested allows a significant reduction in the level of errors of the dielectric constant measurements in weakly absorbing dielectrics if the surface plasmon resonance effects are registered in dependence on the incident frequency, while the SPR is excited at a diffraction grating whose troughs-and-peaks profile is close to harmonical.

Heat flow in the Eurasian, North American and Atlantic regions

The article is a presentation of the research results of the next stage of complex geophysical control of models of deep processes in the tectonosphere of continents and oceans, built by geological theory. Models of the crust and upper mantle are located along a system of profiles encircling the northern hemisphere of the Earth, which have are DSS sections (in some places fragmentary, especially in the oceans). In the first stage, control was performed for density models. It is shown that the gravitational field can always be explained without fitting by calculated effects with discrepancies corresponding to the errors. The second stage focused on thermal models, the effects of which were compared with the observed heat flow (HF) distribution through the surface. Solving the problem is complicated by many features of the manifestation of a nonstationary thermal field. Some of them can be considered as nearsurface interference that needs to be eliminated (but usually this is not done). The work done covered the regions of Eurasia and North America, the Atlantic Ocean, a peripheral fragment of the Pacific Ocean, and transition zones between continents and oceans. Activated and nonactivated platforms, Phanerozoic geosynclines, and rifts were studied on the continents. In transition zones, there are depressions with recent oceanisation, island arcs, and deep9sea trenches. In the oceans, there are basins and the mid9ocean ridge (MOR). In the MOR and some other areas of the World Ocean, the intensity of interference does not allow the use of observed HF for routine monitoring. In other regions, the result was achieved, although often after smoothing out the heat flow field. On the continents, the cases are better, although there are also situations where significant parts of the profiles should simply be excluded from consideration due to an unacceptable level of error. However, here it was possible to confidently demonstrate the correspondence of thermal models of deep processes to experimental HF within the limits of observation and calculation errors.

The effect of baseline on the uncertainties of range determination performed by two-site astrometric observations: A sample case for the triangulation method: TURKSAT 3A and TURKSAT 4A

The uncertainties in range determination depending on two-site locations for GEO satellites were calculated and shown that the uncertainty in the range depends not only on linear baseline distance between the locations but also both latitude and longitude of geographic coordinates of the sites. By taking the first observing site as fixed and changing the location of the second site, the triangulated range calculations were performed by using SGP4 orbital model and published Two-Line Elements (TLE). Additionally, as a sample of triangulated observation, the results of nearly synchronous two-site astrometric measurements of two GEO satellites, TURKSAT 3A and TURKSAT 4A, were presented. These astrometric observations were carried out in TÜBITAK National Observatory (TUG), Antalya and TURKSAT Company’s site, Ankara. Although the baseline between the observatory sites corresponds to a relatively short distance of about 400 km, measured range determinations well stays under the error level expected by Choi et al. (2010).

Image Forgery Detection System using VGG16 UNET Model

The popularity of photography has grown as more individuals have access to camera equipment. Photos seem significant in our daily lives because they are rich with information. However, to learn more, images must often be enhanced. While many technologies are available to enhance the photographs, they are often used to produce phony shots, which leads to the spread of false information. The serious problem of image forgeries has to be addressed. To detect picture fraud, several well-established frameworks have been developed in the past. Recently, there has been an increase in the use of convolutional neural networks (CNNs), which has affected the localization of photo forgeries. One of the most difficult methods of picture falsification is image splicing, which involves cutting a section of one image into another. The picture forgery localization methods based on literature have a lot of drawbacks. As such, developing a technique for accurately and reliably identifying forgeries in photos that have been manipulated is crucial. We provide a potent deep learning-based approach that combines CNN with error level analysis (ELA) to detect picture fraud. To ascertain whether or not a picture has been manipulated, the ELA from an image is extracted and sent to CNN. Transfer learning with UNET (encoder-decoder model), and ELA is used to locate the tampered area. The recommended methods for predicting the changed location. The experiment results on the CASIA 2.0 database are quite encouraging, and these methodologies have been duly evaluated. The results of the recommended model outperform other well-known Transfer learning methodologies compared to the findings. The study suggests that the proposed method might get 0.917 and 0.935 accuracy and precision, respectively. Moreover, the graphical user interface—which enables us to determine the veracity of an image—is designed using these models.

The effect of the viscosity of borehole products on the operation of pumping equipment and the coefficient of oil recovery

The purpose of this work is to develop, create and adapt the technology for the implementation of viscosity determination of the extracted products. The scientific novelty of the work is based on the use of an up-to-date physical and mathematical apparatus for solving problems of effective field development, In the article for the Geppler viscometer to measure the viscosity of wellhead products in field conditions, the principle of viscosity measurement based on measuring the rolling time of a ball in a calibrated tube is proposed. The device allows you to measure the viscosity of both an oil-water medium with a residual amount of dissolved gas and completely degassed products. In laboratory conditions, a universal dependence of the viscosity of well products on the temperature of the liquid and its water content was obtained for oils from a number of fields in the Republic of Tatarstan, which allows calculating viscosity at different temperatures and water levels using a single viscosity measurement. An example of the application of the results of measuring the viscosity of products at the wellhead by a developed device for diagnosing the operation of a well under complicated conditions using a dynamic model, the error level of which allows it to be used and the data obtained to be successfully applied in the development and design of various measures, including those implemented to increase the inter-repair period of well operation. The model allows you to calculate loads and obtain a theoretical dynamogram of the pump's operation on liquids of various viscosities. The results obtained will significantly increase the efficiency of oil recovery and will in one way or another stimulate subsurface users to develop hard-to-recover reserves of liquid hydrocarbons, which will expand the activities of the fuel and energy complex of the Russian Federation.

Should varicocele screening be conducted in men diagnosed with chronic venous insufficiency? A prospective study.

It has been previously proposed in numerous studies that chronic venous insufficiency (CVI) has similar pathogenesis to varicocele in males. Varicocele has been identified as the most common cause of infertility in men, accounting for 40% of cases. This study investigates whether varicocele screening should be conducted in patients with CVI and, if so, which patients should undergo such screening. The study included 102 adult male patients with venous insufficiency complaints who presented to the cardiovascular surgery clinic between January 2023 and June 2023. Data were prospectively collected through medical history interviews and Doppler ultrasound measurements performed by a single radiologist. The relationship between non-normally distributed measurement data of the two groups was evaluated using the Mann-Whitney U test, while the association between categorical variables was assessed using the χ2 test. ROC analysis was employed for determining predictive value. A type 1 error level of α = 0.05 was adopted. The mean left great saphenous vein (GSV) diameter of those with varicocele (6.6 ±2.3) was significantly larger compared to the mean left GSV diameter of those without varicocele (5.3 ±2.6) (p = 0.004). The area under the ROC curve for left GSV diameter was 67% (p = 0.005). When varicocele screening is performed in patients with a left GSV diameter of 5.35 cm and above, sensitivity is 71.4% and specificity is 61.2%. There is a significant association between left GSV diameter and varicocele (p = 0.004). Varicocele screening can be carried out with 71.4% sensitivity in adult male patients with a left GSV diameter of 5.35 cm and above. Both cardiovascular surgeons and radiologists can conduct varicocele screening by measuring pampiniform veins in patients with a left GSV diameter of 5.35 cm and above. This approach has the potential to reduce the incidence of varicocele and associated infertility.

A novel approach to traffic modelling based on road parameters, weather conditions and GPS data using feedforward neural networks

This article presents the development of a estimation model using an artificial neural network to estimate the traffic factor parameter, which reflects changes in travel time for a single transport connection. The modeling of traffic is highly challenging due to the complex and non-linear nature of road systems, the interactions between diverse road users, and the ripple effects of congestion. The research problem addressed is the need to consider a wide range of factors that contribute to congestion, as identified in the literature. To address this challenge, a universal Feedforward Neural Network (FNN) was designed, specifically the Multilayer Perceptron (MLP) 38–10-1 model. The input layer neurons of the MLP receive a vector of input values representing various factors such as road types, technical properties, time of day, days of the week, incidents, weather conditions, and population density. The model was trained using a dataset consisting of 41,945 records of fully completed input variables, extracted from a larger dataset of 300,000 travel time measurements collected from a real transport network mapped on a macro scale (Mazovia, Poland). During the research, the model achieved a satisfactory level of Mean Absolute Percentage Error (MAPE) for the test set (9.12%) and a Normalized Root Mean Squared Error (NRMSE) below 0.02, indicating good estimation performance. Furthermore, this work proposes specialized models with the structure of MLP 34–10-1 for individual types of roads, which also demonstrated satisfactory estimation abilities. These models have practical applications in traffic management and planning. Overall, this research addresses the research problem of modeling factors for predicting travel time changes using an artificial neural network approach. The developed models provide accurate estimations and offer potential applications in transportation systems.

PENGARUH GAYA KEPEMIMPINAN TERHADAP SEMANGAT KERJA KARYAWAN PADA PT. LAJU PERDANA INDAH OKU TIMUR

The leadership style possessed by a person will influence the smooth running of work activities. This research aims to determine the significant influence of leadership style on employee morale. at PT. Laju Perdana Indah East OKU, while the aim of this research is to determine leadership style on employee morale. The hypothesis proposed is that there is a strong relationship between leadership style and employee morale. Data collection techniques were carried out by means of interviews, observation, documentation, and questionnaires as well as literature study. From the calculation results, the number r = 0.249 is obtained. after consulting with conservative standards it turns out that 0.249 is located between 0.200 – 0.399 which is included in low correlation. Then tested with a hypothesis test and obtained to = 0.704 so if it is connected to the t value at a confidence level of 0.95 which means the error level is 0.05, the calculated t is smaller than the t table (0.704 is smaller than 1.860).
 Keywords: Leadership, Spirit

PENGARUH MOTIVASI TERHADAP PRODUKTIVITAS KERJA KARYAWAN PADA CV. MEUBEL MITRA JAYA BELITANG KABUPATEN OKU TIMUR

Motivation is a very important thing in a company, because it can increase employee productivity. Realizing how important motivation is in increasing employee productivity, therefore researchers want to know the problems faced by CV. Meubel Mitra Jaya Belitang East OKU Regency, namely to test how motivation influences employee work productivity. The hypothesis proposed is that motivation has a strong influence on employee work productivity at CV. Mitra Jaya Belitang Furniture, East OKU Regency. Data collection techniques were carried out by means of interviews, observation, documentation, and questionnaires as well as literature study. From the calculation results, the number r = 0.551 is obtained. after consulting with conservative standards it turns out that 0.551 is located between 0.400 – 0.599 which is included in the moderate correlation. Then, to answer the hypothesis test proposed in the previous chapter, whether there is a relationship or not, it is tested using a hypothesis test and it is obtained that to = 1.868, so if it is connected to the t value at a confidence level of 0.95, which means the error level is 0.05, the t count is greater. from the t table (1.868 is greater than 1.860), then the hypothesis proposed is to reject the null hypothesis (Ho) and accept the alternative hypothesis (Ha).
 
 Keywords: Motivation, Productivity

Investigation of the prevalence of potentially malignant and malignant oral lesions in the Southeastern Anatolia Region of Turkey: A 5-year retrospective study

Aim: The aim of this study was to determine the region, frequency, distribution, age, and sex of histopathologically diagnosed oral malignant and oral potentially malignant lesions obtained from patients admitted to the Department of Pathology, Dicle University Faculty of Medicine, Southeastern Anatolia Region of Turkey. Material and Method: The pathological data of oral malignant and potentially malignant lesions histopathologically diagnosed at the Department of Pathology, Dicle University Faculty of Medicine, between 2018 and 2023, were retrospectively reviewed. Potentially malignant and malignant oral lesions were classified, and their distribution according to region, age, and sex was analyzed. The Shapiro-Wilk test was used to analyze the conformity of continuous variables to the normal distribution. The type I error level was accepted as 5% in statistical analyses. Results: Among 161 patients with oral or potential malignancy, 76 (47.2%) were female, and 85 (52.8%) were male, with a mean age of 53.9 ± 17.4 years. The most common lesions were found in the buccal mucosa (40.4%). When 104 malignant lesions were analyzed, the most common lesion was oral squamous cell carcinoma with a rate of 75%, and when 57 potentially malignant lesions were analyzed, 38 (66.7%) of the patients had lichen planus, and 19 (33.3%) had leukoplakia. Conclusion: This retrospective study shows the distribution, frequency, and characteristics of malignant lesions in the oral cavity in a group of populations, especially in the Southeastern Anatolia Region of Turkey, and allows comparison with studies in different populations. How to cite this article: Kaplan B, Alabalık U, Akşahin C, Çolak M, Ortaç H. Investigation of the prevalence of potentially malignant and malignant oral lesions in the Southeastern Anatolia Region of Turkey: A 5-year retrospective study. J Med Dent Invest 2023; 4: e230348. https://doi.org/10.5577/jomdi.e230348

PEMODELAN JUMLAH PENUMPANG PESAWAT DI BANDARA SOEKARNO-HATTA MENGGUNAKAN MODEL HYBRiD SARIMA-FTSMC

The aim of this research is to model the number of airplane passengers at Soelkarno-Hatta airport using a model hybrid SARIMA-FTSMC. The data used in this research is secondary data in the form of data on the number of airplane passengers at Soekarno-Hatta airport from January 2010 to May 2023 which was obtained via the websitebps.go.id. After analyzing the data, the best model was obtained in the SARIMA model, namely SARIMA(1,1,1)(0,1,1)12. Then based on the residual value from the processed data SARIMA will be modeled using the FTSMC model. Next, the residual value of SARIMA(1,1,1)(0,1,1)12 which has been modeled using the FTSMC model is added to the modeling value from SARIMA (1,1,1)(0,1,1)12 known as a modelhybrid SARIMA-FTSMC, with the aim of obtaining a higher level of accuracy or smaller error compared to the SARIMA model. After that, the accuracy level of the model is calculatedhybrid SARIMA-FTSMC uses MAD, MSE, and MAPE. In this research, the level of accuracy of the model was very good, this was shown by the MAPE value being less than 20%.

EVALUATION OF THE EFFECT OF SMOKING ON NESFATIN-1 LEVEL

Aim: Nesfatin-1 is a recently discovered adipocytokine that is believed to regulate food intake and is linked to body mass index. While its precise mechanism of action remains unclear, a deeper understanding of how nesfatin-1 interacts with metabolic diseases, inflammation, and insulin resistance could have significant implications for the treatment of a wide range of conditions, including cardiovascular disease. 
 Smoking is a complex issue with roots in social, cultural, and economic factors that can contribute to nicotine addiction. Additionally, nicotine's ability to stimulate the mind and promote feelings of relaxation can create a positive feedback loop that makes it difficult to quit. Unfortunately, there is limited research on the effects of smoking on Nesfatin-1 levels. However, one study found that women who smoke tend to have lower levels of Nesfatin-1. To build on this finding, the present study aims to further investigate nesfatin-1 levels in both smokers and non-smokers.
 Methods: A total of 70 participants, smokers (n=35) and non-smokers (n=35), were included in the study. The participant's gender, age, height and weight, body mass index, and nesfatin-1 levels were measured and compared.
 
 The SPSS 23.0 program was used to evaluate the data statistically. Data were evaluated with a t-test. The error level was taken as 0.05.
 
 Result: Serum Nesfatin-1 levels were significantly higher in smokers (13.73± 3.11) than in non-smokers (8.63 ± 0.91) (t=-9.315, p<0.01). No significant difference was found between other parameters in the smoker and non-smoker groups.
 
 Conclusion: Our study has shown that individuals who smoke display higher levels of Nesfatin-1 compared to non-smokers, indicating a correlation between smoking and Nesfatin-1. However, further investigation is required to understand the mechanism behind this increase. It is hoped that continued research will unveil the potential of Nesfatin-1 in treating human obesity.

Assessment of aviation accident datasets in severity prediction through machine learning

The importance and seriousness of civil aviation safety have become more noticeable due to the intricate advancement of air transportation. It is crucial to apply diverse datasets to evaluate and anticipate the degree of aviation safety. Data on the different causes of accidents can be analyzed and applied to predict and prevent potential accidents. The main goal of this research is to explore how Machine Learning (ML) techniques can be used to identify correlations and connections between various contributing factors in aviation accidents. It applies ML algorithms on datasets extracted from original data sourced from the National Transportation Safety Board (NTSB) of the United States, Transportation Safety Board (TSB) of Canada, and Australian Transport Safety Bureau (ATSB) aviation accident records spanning from January 2008 to January 2023. Initially, this study uses Artificial Neural Network (ANN), Decision Tree (DT), and Support Vector Machine (SVM) models to predict the civil aviation accident rates for the United States, Canada, and Australia data separately. Sequentially, by extracting Common Features (CF) and reclassifying the Common Sub-Features (CSF) of these three countries, a comprehensive model is created. Finally, it evaluates the differences and limitations of these countries' datasets. The results show that the separate models exhibit a higher level of prediction accuracy and lower errors compared to the common models and the best results (81% accuracy) were achieved through SVM.

Emotional Self-Awareness and Quarter Life Crisis in Final Year of Undergraduate Nursing Students

Background: A quarter-life crisis is when individuals experience an emotional crisis with negative feelings toward the future. Many responsibilities and demands on fourth-year students affect their psychology. A person with good self-awareness makes it easier to control emotions, read the surrounding situation, not be easily affected, and focus on himself. This study aims to analyse the relationship between self-awareness and quarter-life crisis in the final years of undergraduate nursing students. Methods: This research design is correlational with a cross-sectional approach. The sample in this study was 87 people, which was the whole population (Total Sampling). The research instrument used a self-awareness questionnaire and a quarter-life crisis questionnaire—data analysis using the Spearman Rank. Results: The study results showed that most respondents (55.2%) had sufficient emotional self-awareness, and most (52%) experienced a moderate quarter-life crisis. Analysis using the Spearman Rank test obtained a p-value of 0.018 with an error level of α = 0.05, meaning that there is a relationship between emotional self-awareness and quarter-life crisis with a strong category strength (r = -0.54) Conclusion: Some factors affect self-awareness, namely thoughts, feelings, knowledge behaviour, environment, and quarter-life crisis internal factors such as identity exploration, expectations, and religion, while external factors such as romantic relationships, work, family, and friends. Self-introspection strategies can increase self-awareness. Dealing with a crisis is not comparing yourself with others, communicating with parents, or finding professionals if the problem is getting complicated

Standardized viscosity as a source of error in computational fluid dynamic simulations of cerebral aneurysms.

Computational fluid dynamics (CFD) simulations are a powerful tool for studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is infeasible with imaging alone. However, the difficulty of incorporating patient-specific information and inherent obstacles of in vivo validation have limited the clinical usefulness of CFD of cerebral aneurysms. In this work we investigate the effect of using standardized blood viscosity values in CFD simulations of cerebral aneurysms when compared to simulations of the same aneurysms using patient-specific viscosity values derived from hematocrit measurements. The objective of this work is to determine the level of error, on average, that is, caused by using standardized values of viscosity in CFD simulations of cerebral aneurysms. By quantifying this error, we demonstrate the need for incorporating patient-specific viscosity in future CFD investigations of cerebral aneurysms. CFD simulations of forty-one cerebral aneurysms were conducted using patient-specific boundary conditions. For each aneurysm two simulations were conducted, one utilizing patient-specific blood viscosity derived from hematocrit measurements and another using a standardized value for blood viscosity. Hemodynamic parameters such as wall shear stress (WSS), wall shear stress gradient (WSSG), and the oscillatory shear index (OSI) were calculated for each of the simulations for each aneurysm. Paired t-tests for differences in the time-averaged maps of these hemodynamic parameters between standardized and patient-specific viscosity simulations were conducted for each aneurysm. Bland-Altman analysis was used to examine the cohort-wide changes in the hemodynamic parameters. Subjects were broken into two groups, those with higher than standard viscosity and those with lower than standard viscosity. An unpaired t-test was used to compare the percent change in WSS, WSSG, and OSI between patient-specific and standardized viscosity simulations for the two cohorts. The percent changes in hemodynamic parameters were correlated against the direction and magnitude of percent change in viscosity, aneurysm size, and aneurysm location. For all t-tests, a Bonferroni-corrected significance level of 0.0167 was used. 63.2%, 41.5%, and 48.7% of aneurysms showed statistically significant differences between patient-specific and standardized viscosity simulations for WSS, WSSG, and OSI respectively. No statistically significant difference was found in the percent changes in WSS, WSSG, and OSI between the group with higher than standard viscosity and those with lower than standard viscosity, indicating an increase in viscosity can cause either an increase or decrease in each of the hemodynamic parameters. On a study-wide level no significant bias was found in either direction for WSS, WSSG, or OSI between the simulation groups due to the bidirectional effect of changing viscosity. No correlation was found between percent change of viscosity and percent change of WSS, WSSG, or OSI, meaning an after-the-fact correction for patient-specific viscosity is not feasible. Standardizing viscosity values in CFD of cerebral aneurysms has a large and unpredictable impact on the calculated WSS, WSSG, and OSI when compared to CFD simulations of the same aneurysms using a patient-specific viscosity. We recommend implementing hematocrit-based patient-specific blood viscosity values for all CFD simulations of cerebral aneurysms.

Type I error and power rates: A comparative analysis of techniques in differential item functioning

The main purpose of this study is to examine the Type I error and statistical power ratios of Differential Item Functioning (DIF) techniques based on different theories under different conditions. For this purpose, a simulation study was conducted by using Mantel-Haenszel (MH), Logistic Regression (LR), Lord’s χ2, and Raju’s Areas Measures techniques. In the simulation-based research model, the two-parameter item response model, group’s ability distribution, and DIF type were the fixed conditions while sample size (1800, 3000), rates of sample size (0.50, 1), test length (20, 80) and DIF- containing item rate (0, 0.05, 0.10) were manipulated conditions. The total number of conditions is 24 (2x2x2x3), and statistical analysis was performed in the R software. The current study found that the Type I error rates in all conditions were higher than the nominal error level. It was also demonstrated that MH had the highest error rate while Raju’s Areas Measures had the lowest error rate. Also, MH produced the highest statistical power rates. The analysis of the findings of Type 1 error and statistical power rates illustrated that techniques based on both of the theories performed better in the 1800 sample size. Furthermore, the increase in the sample size affected techniques based on CTT rather than IRT. Also, the findings demonstrated that the techniques’ Type 1 error rates were lower while their statistical power rates were higher under conditions where the test length was 80, and the sample sizes were not equal.

Error-Aware, Layer-Resolved Characterisation of Lithium-Ion Batteries Based on Ultrasonic Resonance and Parametric Analysis

With the prevalence of electrification in transportation and grid storage sectors, lithium-ion batteries (LIBs) are becoming one of the most fundamental energy storage elements and undergoing a profound trend of performance upscaling. The upscaled batteries demand next-level characterisation methodologies, and particularly appealing is the capability to resolve inner structural and morphological information physically, so as to identify the internal state and evolutions precisely and cost-effectively. In recent years, ultrasonic measurements have been proven as promising candidates for probing and inspecting LIBs. However, such approaches can only measure peripheral geometric features at a cell-level resolution and their characterisation performances tend to be subject to empirical configurations and sensitive to measurement conditions. To address these issues, this work reports an ultrasonic resonance-based method, featuring reliable characterisation performance, to realise layer-level robust inversion of the layered structure within LIBs. Firstly, a generalised theoretical model is introduced to capture the interaction characteristics between the ultrasound and the multilayer structure inside LIBs. By incorporating the captured characteristics into the analytic-signal procedure, a systematical framework is established to retrieve the stacking order, individual thickness, and local geometry information in a layer-resolved manner1, 2. Then, the relationship between the measurement parameters and the characterisation performance is analytically investigated. By considering both the temporal and spatial metrics, the performance evaluation indices are determined, with the critical measurement parameters recognised according to their physical significance. After that, the impacts of measurement parameters on the characterisation performance of LIBs are thoroughly studied by carrying out parametric analysis on the response signal simulated by the ultrasonic resonance model. Guided by such a relationship, an optimal strategy for parameter selection is developed to ascertain reliable characterisation, with its level of errors being predictable. Finally, experimental studies are carried out on different batteries with the ground truth obtained by the micro X-ray computed tomography, and the effectiveness and reliability of the proposed characterisation method are carefully validated. The proposed method demonstrates reliable performance in characterising layered structure within LIBs and could pave the way for developing performance-informed monitoring and prediction algorithms for state of health and state of safety estimations of LIBs. References M. Huang, N. Kirkaldy, Y. Zhao, Y. Patel, F. Cegla, and B. Lan, Journal of Energy Storage, 50 104585 (2022).R. A. Smith, L. J. Nelson, M. J. Mienczakowski, and P. D. Wilcox, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 65 (2), 231-243 (2018).

A cascade fuzzy adaptive based interaction torque control of a pneumatically actuated forearm rehabilitation robot under disturbance effects

In this study, an intelligent adaptive interaction torque control for a pneumatically actuated forearm rehabilitation robot has been proposed. The main objective is to provide a haptic environment that ensures stable interaction torque fields at changing levels. To achieve this goal, a cascade fuzzy adaptive controller, that is specifically tailored to handle varying levels of interaction torque and ensure stability throughout the rehabilitation process, has been designed. To improve the efficiency of the controller, non-linear friction torque identification of the pneumatic actuator based on changing operating conditions has been conducted. Parallel to this, a user motion intention detection algorithm has been designed to provide compliant, safe and suitable human-robot interactions. The disturbance cases have been considered to make the system robust to unknown conditions. Stability analysis has been performed, specifically focusing on the boundary-input boundary-output (BIBO) stability conditions. In order to demonstrate the superior performance of the proposed cascade fuzzy adaptive algorithm, a cascade PID algorithm has also been meticulously designed for comparison. Numerous experimental validation tests involving a healthy user were conducted in a Hardware-in-the-Loop environment, focusing on torque trajectory tracking performance. The proposed control technique exhibited improved convergence dynamics compared to the cascade PID algorithm, yielding mean absolute error levels of 0.0218 Nm and 0.099 Nm for target interaction torque under disturbance-free and disturbed conditions, respectively.