Comparison of test performance on paper-based testing (PBT) and computer-based testing (CBT) by English-majored undergraduate students in China

Computer-based testing (CBT), which refers to delivering assessments with computers, has been widely used in large English proficiency tests worldwide. Despite an increasing CBT in China, limited research is available concerning whether CBT can be used for the Test for English Majors-Band 4 (TEM 4). The current study investigated whether testing mode impacted TEM 4 score and factors (i.e., computer familiarity level and attitude towards CBT) that might correlate with performance on CBT of TEM 4. Overall 92 Chinese undergraduate students were randomly assigned to one of the groups, i.e., CBT or paper-based testing (PBT), and took the test. A mixed method was employed, including (1) quantitative and qualitative analysis of test performance in two modes, as well as CBT group participants’ computer familiarity and attitudes towards the mode; and (2) thematic analysis of semi-structured interviews. The results revealed that (1) test scores in CBT and PBT were comparable; (2) two items in the computer familiarity questionnaire, i.e., comfort level of reading articles on the computer and forgetting time when using computers, positively correlated with CBT scores; and (3) participants’ attitude towards CBT did not impact test performance.

Method of verifying the emission level of the exhaust components of a special vehicle in relation to EURO III standard in road conditions

The following article presents the method of verification of EURO III standard in real life conditions for special vehicles. The test object qualified as a special vehicle of N3G category was tested in road conditions along a defined route, and then the obtained measurement results were compared to the exhaust emission standard (EURO III) applicable for this vehicle in transient testing mode. A method of comparing the emission factors in road conditions with the indicators obtained on the engine dynamometer was proposed. An AVL mobile exhaust gas analyzers (PEMS) dedicated for the Real Driving Emissions (RDE) road tests were used in the research.

Developing an Algorithm for Determining Malfunctions in the Measuring Channels of the Acoustic Leak Control System

Nowadays Russian and foreign NPP operate systems for monitoring coolant leakage at the primary circuit based on measuring the dispersion of generated acoustic signals (acoustic waves) propagating over the metal surface. In the acoustic leak monitoring systems provision are made to self-diagnosis of measuring channels, as well as an adaptive algorithm is applied that allows automatic readjusting to the use of neighboring measuring channels instead of those that have failed. At the same time, there may be such malfunctions in the system technical means that do not automatically diagnose the malfunction of the measuring channels, which may lead to the failure of the system function to determine the magnitude and coordinate of the leak of the primary circuit coolant. That is why, the task of developing algorithms for determining the malfunction of the measuring channels of the acoustic leak monitoring system, implemented using software without making changes to the technical means of the system, is urgent. An algorithm is proposed for determining the malfunction of the measuring channels of the acoustic leak control system using a test signal of increased duration. An analysis of the applicability of the algorithm was performed on a representative sample of signals from measuring channels of the acoustic leak monitoring system of campaign 2018--2019 Novovoronezh NPP-2 рower Unit no. 1. The proposed algorithm has been implemented in the testing mode at power Unit no. 1 of Novovoronezh NPP-2 since the start of a new campaign in July 2019

‘Hippocrates’ – support system for medical decision-making for primary care for early detection of socially significant diseases

Within the framework of the Federal Project ‘Creation of a unified digital contour in health care based on the unified state information system of health care’ of the National Project ‘Healthcare’, employees of the Moscow State Medical and Dental University n.a. A. I. Evdokimov (Department of Therapy, Clinical Pharmacology and Emergency Medicine) with the assistance of RPO ‘Outpatient Doctor’ in 2020, a system for supporting medical decisions was created. The program ‘Hippocrates’ works in the testing mode, but now it is fulfilling the tasks assigned to it to increase the early detection of chronic diseases, and it also plays an important role in teaching doctors to take action based on clinical guidelines.

SVM Performance for Predicting the Effect of Horizontal Screen Diameters on the Hydraulic Parameters of a Vertical Drop

The present study investigated the application of support vector machine algorithms for predicting hydraulic parameters of a vertical drop equipped with horizontal screens. The study incorporated varying sizes of a rectangular channel. Horizontal screens, in addition to being able to dissipate the destructive energy of the flow, cause turbulence. The turbulence in turn supplies oxygen to the system through the promotion of air–water mixing. To achieve the objectives of the present study, 164 experiments were analyzed under the same experimental conditions using a support vector machine. The approach utilized dimensionless terms that included scenario 1: the relative energy consumption and scenario 2: the relative pool depth. The performance of the models was evaluated with statistical criteria (RMSE, R2 and KGE) and the best model was introduced for each of the parameters. RMSE is the root mean square error, R2 is the correlation coefficient and KGE is the Kling–Gupta criterion. The results of the support vector machine showed that for the first scenario, the third combination with R2 = 0.991, RMSE = 0.00565 and KGE = 0.998 for the training mode and R2 = 0.991, RMSE = 0.00489 and KGE = 0.991 for the testing mode were optimal. For the second scenario, the third combination with R2 = 0.988, RMSE = 0.0395 and KGE = 0.998 for the training mode and R2 = 0.988, RMSE = 0.0389 and KGE = 0.993 for the testing mode were selected. Finally, a sensitivity analysis was performed that showed that the yc/H and D/H parameters are the most effective parameters for predicting relative energy dissipation and relative pool depth, respectively.

Perbandingan Performansi Kinerja Algoritma Pengklasifikasian Terpandu Untuk Kasus Penyakit Kardiovaskular

One of the health problems that occur in Indonesia is the increasing number of NCD (Non-Communicable Disease) such as heart attack and cardiovascular disease. There are two factors that cause cardiovascular disease, i.e. factor that can be changed and cannot be changed. This study aim to analyze the best performance of several classification algorithms such as k-nearest neighbors algorithm (k-NN), stochastic gradient descent (SGD), random forest (RF), neural network (NN) and logistic regression (LR) in classifying cardiovascular based on factors that caused those diseases. There are two aspects that need to be examined, the performance of each algorithm which is evaluated using the Confusion matrix method with the parameters of accuracy, precision, recall and AUC (Area Under the Curve). The dataset uses 425.195 samples from result data of cardiovascular disease diagnosed. The testing mode uses percentage split and cross-validation technique. The experimental results show that the performance of NN algorithms produces the best prediction accuracy compared to other algorithms, which is accuracy of 89.60%, AUC of 0.873, precision of 0.877, and recall of 0.896 using percentage split and cross-validation testing mode using Orange. For the accuracy of 89.46%, AUC of 0.865, precision of 0.875, and recall of 0.895 using cross-validation testing mode using Weka. By KNIME, the result of accuracy value is 88.55%, AUC value is 0.768, precision value is 0.854, and recall value is 0.886 using cross-validation testing mode.

The Ways of Reaching the Specified Mode of Testing Samples for Torsion with Variable Strain Rate

The paper is devoted to the practical implementation of the new torsion testing method for studying rheological properties of materials in a hot state. This method involves the testing of cylindrical samples in the grips of a test setup, the angular velocity of which changes exponentially. The testing mode allows you to restore the hardening curves of a material according to the test results. This article aims to formulate the requirements for possible ways to implement the proposed testing method, and presents two different ways to obtain the specified exponential testing mode. The experience of their use on the test setup in the Ural Federal University indicates the feasibility of the new testing method, as well as the possibility of a smooth transition to the specified testing mode.