The Physics Laboratory Works – Individualized Computer Simulations

The physics laboratory-works creating and operating computer simulations experience is described. A significant amount of laboratory works can be classified as a “black box”. The studied physical phenomenon is hidden from direct observation, the control is carried out by means of electrical measuring devices. It is difficult to distinguish physical reality from its imitation when performing such work, so the virtualization of this one does not require realistic images. The schematic representation of the laboratory installation greatly simplifies the process of creating a simulator. A unique set of installation parameters is formed for each student performing laboratory work on the simulator, which contributes to the independence of the student's work. These parameters are stored in Google Sheets. Their transfer to the laboratory work’s html-template is carried out in encrypted form through the Google Apps Script service. Virtual laboratory work is implemented as a cross-platform web application.

A Black Hole-Aided Deep-Helix Channel Model for DNA

In this article, we present a black-hole-aided deep-helix (bh-dh) channel model to enhance information bound and mitigate a multiple-helix directional issue in Deoxyribonucleic acid (DNA) communications. The recent observations of DNA do not match with Shannon bound due to their multiple-helix directional issue. Hence, we propose a bh-dh channel model in this paper. The proposed bh-dh channel model follows a similar fashion of DNA and enriches the earlier DNA observations as well as achieving a composite like information bound. To do successfully the proposed bh-dh channel model, we first define a black-hole-aided Bernoulli-process and then consider a symmetric bh-dh channel model. After that, the geometric and graphical insight shows the resemblance of the proposed bh-dh channel model in DNA and Galaxy layout. In our exploration, the proposed bh-dh symmetric channel geometrically sketches a deep-pair-ellipse when a deep-pair information bit or digit is distributed in the proposed channel. Furthermore, the proposed channel graphically shapes as a beautiful circulant ring. The ring contains a central-hole, which looks like a central-black-hole of a Galaxy. The coordinates of the inner-ellipses denote a deep-double helix, and the coordinates of the outer-ellipses sketch a deep-parallel strand. Finally, the proposed bh-dh symmetric channel significantly outperforms the traditional binary-symmetric channel and is verified by computer simulations in terms of Shannon entropy and capacity bound.

Термодинамические свойства жидкого цезия: поиск аномалий

The polymorphism of liquid cesium at atmospheric pressure in the temperature range of ~ 590 K in the form of a second-order phase transition, announced in the late 90s, is not confirmed in new experimental works and in computer simulations of its properties. At the same time, the question whether the change in the properties of liquid cesium with a decrease or increase in density up to two times is monotonous or is accompanied by various anomalies needs further research.

On the Mechanism of the Dyotropic Expansion of Hydrindanes into Decalins

A combined computational/experimental approach has revealed key mechanistic aspects in a recently reported dyotropic expansion of hydrindanes into decalins. While computer simulations had already anticipated the need for acid catalysis...

Use of Computer Simulations for the Understanding and Retention of Mathematical Concepts

Simulations provide unique features and instructional benefits for the improved understanding of concepts. This study aimed to find the effect of computer simulations on the understanding and retention of mathematical concepts. This was an experimental research. A sample of 100 students participated in this experimental research. The sample was further distributed into an equal number of students in two groups. Some topics were selected from the grade–IX mathematics textbook. The selected mathematical topics were taught to the control group by lecture method whereas computer simulations were used for teaching mathematical concepts to the experimental group. Data analysis showed that in the posttest, the experimental group performed better than the control group at a 0.05 level of significance. The scores of the retention test of the experimental group were also found better than the control group. It is recommended to include computer simulations in the teaching-learning process for better comprehension of abstract concepts of mathematics. Keywords: Achievement, Mathematical Concepts, Retention, Simulations

Diagnosis of interior damage with a convolutional neural network using simulation and measurement data

Current deep learning applications in structural health monitoring (SHM) are mostly related to surface damage such as cracks and rust. Methods using traditional image processing techniques (such as filtering and edge detection) usually face difficulties in diagnosing internal damage in thicker specimens of heterogeneous materials. In this paper, we propose a damage diagnosis framework using a deep convolutional neural network (CNN) and transfer learning, focusing on internal damage such as voids and cracks. We use thermography to study the heat transfer characteristics and infer the presence of damage in the structure. It is challenging to obtain sufficient data samples for training deep neural networks, especially in the field of SHM. Therefore we use finite element (FE) computer simulations to generate a large volume of training data for the deep neural network, considering multiple damage shapes and locations. These computer-simulated data are used along with pre-trained convolutional cores of a sophisticated computer vision-based deep convolutional network to facilitate effective transfer learning. The CNN automatically generates features for damage diagnosis as opposed to manual feature generation in traditional image processing. Systematic parameter selection study is carried out to investigate accuracy versus computational expense in generating the training data. The methodology is demonstrated with an example of damage diagnosis in concrete, a heterogeneous material, using both computer simulations and laboratory experiments. The combination of FE simulation, transfer learning and experimental data is found to achieve high accuracy in damage localization with affordable effort.