Research on Traffic Detection Method of Secure Transmission Industrial Internet of Things Based on Computer Vision

In recent years, the process of industrial modernization has intensified, traditional industrial control has been improved and rapidly developed, industrial automation and intelligent unmanned production lines have become a new development trend, and the Internet of Things has become the basic direction of industrial development. In order to improve the effect of safe transmission and industrial IoT traffic detection, this study uses a neural network to improve the industrial IoT traffic detection algorithm. In order to improve the visualization effect of monitoring, this study uses computer vision technology to construct a traffic detection system of secure transmission industrial Internet of Things and builds an intelligent detection model. Finally, this study combines experimental research to verify the performance of the system. From the statistical point of view, it can be seen that the system’s security detection and traffic detection effects are very good.

IMPACT OF TRANSFER PRICING ON FOREIGN DIRECT INVESTMENT IN ROMANIA

The purpose of the study presented in this paper is to analyse the impact of transfer pricing on foreign direct investment (FDI) in Romania. For attaining this goal, we performed a simple linear regression by the least squares method to study the impact of adjustments of tax obligations in the field of transfer pricing on foreign direct investment in the period 2011-2019.We have proved, from a statistical point of view, that there is a relationship between foreign direct investment and adjustments to tax liabilities resulting from transfer pricing

Age-Related, Sport-Specific Dysfunctions of the Shoulder and Pelvic Girdle in Athletes Table Tennis Players. Observational Study

Background: Postural skills are fundamental in motor activities, so far no evidence of a direct relationship has been found, it is therefore recommended to consider the following directions, the higher the level of sports competition, the better the body posture; or better athletes also have a better body posture. Around the age of 11-14 years, it is a period of aggressive development, if the rapid growth of the bone system is not associated and symmetrical with the development of soft tissues serious postural deficiencies may develop in table tennis players. Methods: We used the web camera – photographic method (38) related to the Sensor Medica software that allows the acquisition of images in order to detect postural deficiencies and we considered it necessary to have a clear image of the level of technical-tactical training of female juniors III using 5 tests specific to topspin attack in order to assess the influence of body posture on such tests. Eighteen female juniors III (the mean ± SD age, height and weight were 11.1 ± 0.2 years, 147.7 ± 2.6 cm, 39.0 ± 2.0 kg). Descriptive statistical analysis was performed on the procedures for establishing the normality of data distribution, Levene's Test for Equality of Variances, the t test for independent samples. The confidence interval was set at 95% (p < 0.05), Results and Conclusions: Since Sig. (2-tailed) or p < α = 0.001 and taking into account that the confidence interval limits for the difference between the sample mean and the reference value (95% CI for the mean difference) do not contain the zero value, it is accepted that there are statistically significant differences between the shoulder inclination for the female athletes in the sample studied and the reference value. We identified that at the level of alignment between anatomical landmarks, the percentage of deficiency of the entire lot of female juniors III in the case of shoulders is 100% and at the level of PSIS is 66%, which validates several studies that stated that in this period of aggressive growth correlated with repetitive unilateral executions specific to the topspin attack lead to postural deficiencies. In terms of the influence of body posture on the quality level, we identified that Group 1 – (without PSIS imbalance) has a higher average overall efficiency of the 5 tests (11.33) compared to Group 2 (8.58), even if from a statistical point of view these differences are not significant. Keywords: Body posture, Asimmetry, Topspin attack, Table tennis, Sensor Medica,

The Evolution of AI-Driven Educational Systems during the COVID-19 Pandemic

COVID-19 had a major impact on education, substantially stimulating the need for digital remote education. From paperback books to PDFs, from physical classes to e-conferencing, and from various traditional mechanisms of information transmission to systems that are driven by artificial intelligence and use adaptive learning approaches, all of these had to be adopted by both teachers and students. This paper analyzes the use of an adaptive learning system before and during the COVID-19 pandemic from a statistical point of view on a set of data gathered in Romania during a pilot project. The main data inputs are the number of students that enrolled for a certain course, the percentage of students that successfully completed it, and information about their age group, location and main area of interest. Our study finds that the use of artificial intelligence has increased during the COVID-19 pandemic and, by analyzing the data obtained during the study, we managed to prove that artificial-intelligence-driven tools and systems have gained traction among all the parties involved in the educational process.

Collecting Microplastics in Gardens: Case Study (i) of Soil

As an emerging contaminant, microplastic is receiving increasing attention. However, the contamination source is not fully known, and new sources are still being identified. Herewith, we report that microplastics can be found in our gardens, either due to the wrongdoing of leaving plastic bubble wraps to be mixed with mulches or due to the use of plastic landscape fabrics in the mulch bed. In the beginning, they were of large sizes, such as &gt; 5 mm. However, after 7 years in the garden, owing to natural degradation, weathering, or abrasion, microplastics are released. We categorize the plastic fragments into different groups, 5 mm–0.75 mm, 0.75 mm–100 μm, and 100–0.8 μm, using filters such as kitchenware, meaning we can collect microplastics in our gardens by ourselves. We then characterized the plastics using Raman image mapping and a logic-based algorithm to increase the signal-to-noise ratio and the image certainty. This is because the signal-to-noise ratio from a single Raman spectrum, or even from an individual peak, is significantly less than that from a spectrum matrix of Raman mapping (such as 1 vs. 50 × 50) that contains 2,500 spectra, from the statistical point of view. From the 10 g soil we sampled, we could detect the microplastics, including large (5 mm–100 μm) fragments and small (&lt;100 μm) ones, suggesting the degradation fate of plastics in the gardens. Overall, these results warn us that we must be careful when we do gardening, including selection of plastic items for gardens.

Quantitative Analysis Regarding the Incidents to the Pipelines of Petroleum Products for an Efficient Use of the Specific Transportation Infrastructure

The transportation infrastructure for petroleum products contains complex pipeline systems, developed on a global scale and totaling investments of hundreds of millions of dollars. The operation and maintenance of these systems have to be performed in relation to the analysis of incidents of various types, which take place in various areas of the world. The present paper aims to analyze in as much detail as possible, from a statistical point of view, the case of the pipeline system for petroleum products in Romania in order to streamline the operation of this critical infrastructure for Romania. Through the statistical tools, we established the hierarchies of the causes of the analyzed incidents, weights of the effects generated by these sources of accidents, and correlations between various parameters, in order to create a useful plan of measures and actions in the efficient operation of the pipeline system. The importance and topicality of the subject is also demonstrated by the major negative impact of the accidents in this sector, through product leaks from pipes in the soil and in watercourses, which generate significant pollution values, thus influencing the balance of the environment.

Electrochemical Determination of Chlorogenic Acid in Nutraceuticals Using Voltammetric Sensors Based on Screen-Printed Carbon Electrode Modified with Graphene and Gold Nanoparticles

The present study describes the electrochemical properties of three screen-printed electrodes (SPEs), the first electrode being carbon-based (C), the second graphene-based (GPH), and the third based on GPH modified with gold nanoparticles (GNP). These electrodes were used for the study of the electrochemical behavior of chlorogenic acid in different aqueous solutions, at pH = 7. In chlorogenic acid solution, a redox process was noticed in the case of all three electrodes; GPH and GNP significantly improved the sensor response regarding sensitivity and reversibility, a fact demonstrated by characterizing the sensor by cyclic voltammetry in potassium ferrocyanide, which corresponds to the exchange of two electrons and two protons. Moreover, the calibration curves for each sensor were developed, subsequently calculating the detection limits (LOD) and the quantification limits (LOQ). Low LOD and LOQ were obtained, the best—of the order of 10−7 M (LOD = 0.62 × 10−7 M; LOQ = 1.97 × 10−7 M)—being obtained in the case of GPH-GNP-SPE, which demonstrates that the method may be applied for determining chlorogenic acid in real samples. Thus, the sensors were successfully used for the quantitative determination of chlorogenic acid in three nutraceutical products. The validation of the results was done using the FTIR method. The results obtained by cyclic voltammetry were in accordance with those obtained by the spectrometric method, without significant differences from a statistical point of view.

Symmetric and Asymmetric Diffusions through Age-Varying Mixed-Species Stand Parameters

(1) Background: This paper deals with unevenly aged, whole-stand models from mixed-effect parameters diffusion processes and Voronoi diagram points of view and concentrates on the mixed-species stands in Lithuania. We focus on the Voronoi diagram of potentially available areas to tree positions as the measure of the competition effect of individual trees and the tree diameter at breast height to relate their evolution through time. (2) Methods: We consider a bivariate hybrid mixed-effect parameters stochastic differential equation for the parameterization of the diameter and available polygon area at age to ensure a proper description of the link between them during the age (time) span of a forest stand. In this study, the Voronoi diagram was used as a mathematical tool for the quantitative characterization of inter-tree competition. (3) Results: The newly derived model considers bivariate correlated observations, tree diameter, and polygon area arising from a particular stand and enables defining equations for calculating diameter, polygon-area, and stand-density predictions and forecasts. (4) Conclusions: From a statistical point of view, the newly developed models produced acceptable statistical measures of predictions and forecasts. All the results were implemented in the Maple computer algebra system.

Prediction of Genetic Factors of Hyperthyroidism Based on Gene Interaction Network

The number of hyperthyroidism patients is increasing these years. As a disease that can lead to cardiovascular disease, it brings great potential health risks to humans. Since hyperthyroidism can induce the occurrence of many diseases, studying its genetic factors will promote the early diagnosis and treatment of hyperthyroidism and its related diseases. Previous studies have used genome-wide association analysis (GWAS) to identify genes related to hyperthyroidism. However, these studies only identify significant sites related to the disease from a statistical point of view and ignore the complex regulation relationship between genes. In addition, mutation is not the only genetic factor of causing hyperthyroidism. Identifying hyperthyroidism-related genes from gene interactions would help researchers discover the disease mechanism. In this paper, we purposed a novel machine learning method for identifying hyperthyroidism-related genes based on gene interaction network. The method, which is called “RW-RVM,” is a combination of Random Walk (RW) and Relevance Vector Machines (RVM). RW was implemented to encode the gene interaction network. The features of genes were the regulation relationship between genes and non-coding RNAs. Finally, multiple RVMs were applied to identify hyperthyroidism-related genes. The result of 10-cross validation shows that the area under the receiver operating characteristic curve (AUC) of our method reached 0.9, and area under the precision-recall curve (AUPR) was 0.87. Seventy-eight novel genes were found to be related to hyperthyroidism. We investigated two genes of these novel genes with existing literature, which proved the accuracy of our result and method.

ANALYSIS OF THERMOLUMINESCENCE GLOW CURVES RECORDED UNDER THE HYPERBOLIC HEATING SCHEME BY USING AN ALTERNATIVE CONCEPT OF SYMMETRY

Usually, the order of kinetics of thermoluminescence (TL) glow curve is evaluated by using the concept of traditional symmetry factor (μ_g) in which only three points of a glow curve are used. From the statistical point of view of the reliability of any method of analysis of glow, curve improves if instead of a few points the method can use a larger portion of the glow curve. In the present work, a technique is proposed to determine the order of kinetics associated with a TL peak by using the concept of skewness. The method is applied to experimental thermoluminescence (TL) curves recorded in a hyperbolic heating scheme.