Ex) Article Title, Author, Keywords
pISSN 0374-4914
eISSN 2289-0041
pISSN 0374-4914
eISSN 2289-0041
Ex) Article Title, Author, Keywords
Abstract : The first steam engine, the Aeolipile, was powered by action–reaction and rotational forces. This study presented the Aeolipile model experiments ‘Spinning water bottle’ and ‘Spinning straw’ to gifted science students and instructed them to generate corresponding explanatory models. Results showed that the gifted students most commonly provided explanatory models that explain the spinning phenomenon based on the concept of action–reaction. Additionally, the most common groups included students who either maintained a level 3 model that correctly explained the rotational phenomenon based on the law of action and reaction or progressed to a level 4 model that discusses the rotational phenomenon based on the law of action and reaction and rotational force. This finding confirms that science-gifted students can generate explanatory models for the Aeolipile model based on their comprehension of the law of action and reaction. Moreover, the generation of explanatory models for the ‘Spinning straw’ experiment can aid science-gifted students in comprehending and expressing rotational forces.
Abstract : The nonlinear evolution of large scale structures (LSSs) can disclose key cosmological information for understanding the physics beyond the standard model. In recent years, the use of deep neural networks in the direct extraction of cosmological information from LSS maps has gained increasing attention among research community. As the evolution of LSSs is governed by a growth factor that depends on contents of the universe combined with nonlinear effects, if neural networks can capture correlations at various epochs, then precision measurements of cosmological parameters can be improved. In this paper, we perform N-body simulations and demonstrate that image-based transformer networks configured for time-series data can be enhanced for the accurate extraction of Ωm and σ8 parameters.
Abstract : In this study, we explore the spectral discrimination of fluorescence images of liquid scintillators acquired by complementary metal oxide semiconductor (CMOS) image sensors using the discriminative ability of deep convolutional neural networks without requiring any special effort. With the continuous advancement of semiconductor fab-processing technology, the processing technology of optical elements in image sensors has also advanced. However, there exists a trade-off between the pixel size of an image sensor, signal noise ratio, and high color reproduction. Furthermore, commercial CMOS image sensor manufacturers typically do not provide users with spectral response data for their CMOS sensors. To address these challenges, we generated training images using a light-emitting diode module programmable on a single-board computer and demonstrated the feasibility of inferring the spectral response backward from the discriminant values of a deep convolutional neural network. Building on the previous study and considering the operational characteristics of neutrino experiments, we evaluated the feasibility of employing a deep convolutional neural network for monitoring the attenuation distance and spectral response of light in a liquid scintillator through supervised learning. In future, we aim to optimize transformer implantation that is efficient with limited required computational resources for the characteristics of the Internet of Things.
Abstract : The optical properties of white light-emitting diodes (LEDs) with a yellow phosphor plate and a red quantum dot film applied sequentially on top of a blue LED chip were investigated as a function of phosphor thickness, quantum dot concentration, and the presence or absence of the microprism film. It was found that an excessively thick yellow phosphor plate leads to an increased absorption of the blue LED, resulting in a higher proportion of yellow light and deviation from the Planckian locus. This deviation arises due to the absence of long-wavelength red component in the emitting spectrum of yellow phosphor plates. Particularly, the application of one-dimensional microprism film to the quantum dot film demonstrates notable enhancement. The reflection at the prism interface facilitates the reciprocating motion of light within the vertical cavity formed by the prism film and the bottom reflector. This phenomenon considerably increases the color conversion efficiency of the red quantum dot film, resulting in improved on-axis brightness and color rendering index. This study provides insights into improving the color rendering performance of lighting with remote color-changing components.
Abstract : The structure of physics education research papers was explored by analyzing and comparing empirical research papers from academic fields closely related to physics education research. A total of 100 papers were studied, including 20 studies each in physics, chemistry, education, and psychology, all of which were recently published in Korean journals. According to the results, IM[RD]C for physics and chemistry, ILMR[DC] for education, and IMRD for psychology were the most common. However, structural patterns in physics education were found to be diverse. Moreover, titles such as “Conclusions and suggestions” toward the end of the paper was identified as a characteristic trait of physics education papers as it was rarely observed in other fields. As in education, tables were used more often than pictures and the characteristics of natural and social science research articles appeared complex in physics education papers. Furthermore, some characteristics were unique to physics education papers.
Abstract : The combination of LaVO3 and porous Si (PSi) materials show a high absorption in the ultraviolet to visible range and is a remarkable architecture for high-performance broadband photodetectors (PDs). In this study, we introduced a LaVO3/PSi heterojunction device. The LaVO3/PSi PD exhibits the highest photocurrent/dark current characteristics at 0 V, which indicates that it is “self-powered.” Furthermore, this device shows a photoresponsivity/detectivity of 0.4 AW−1/1.6 × 1012 cm Hz1/2 W−1 at a wavelength of 830 nm. Moreover, the linear dynamic range and rise/fall times of the device are 68 dB and 48/53 µs, respectively. These results are expected to enable the application of the simple LaVO3/PSi heterojunction structure as a next-generation self-powered optoelectronic device.
Abstract : Photomultiplier tubes (PMTs) are widely used in particle physics experiments, such as neutrino precision measurement and dark matter search to observe events. Thus, the stable performance of PMTs is essential in such experiments. The stable operation and high-voltage monitoring are some of the most important factors. This paper reports a program that chronologically stores values provided by high-voltage suppliers in a database and visually monitors the currently given values simultaneously.
Abstract : The first steam engine, the Aeolipile, was powered by action–reaction and rotational forces. This study presented the Aeolipile model experiments ‘Spinning water bottle’ and ‘Spinning straw’ to gifted science students and instructed them to generate corresponding explanatory models. Results showed that the gifted students most commonly provided explanatory models that explain the spinning phenomenon based on the concept of action–reaction. Additionally, the most common groups included students who either maintained a level 3 model that correctly explained the rotational phenomenon based on the law of action and reaction or progressed to a level 4 model that discusses the rotational phenomenon based on the law of action and reaction and rotational force. This finding confirms that science-gifted students can generate explanatory models for the Aeolipile model based on their comprehension of the law of action and reaction. Moreover, the generation of explanatory models for the ‘Spinning straw’ experiment can aid science-gifted students in comprehending and expressing rotational forces.
Abstract : Chat GPT was released in 2022; since then, generative artificial intelligence (AI) has gained attention for its potential applications in various fields, including education. This paper explored how preservice physics teachers can use Chat GPT in lesson preparation and execution. Chat GPT was introduced to 22 preservice physics teachers, and they were encouraged to use it in their education planning and implementation. The included preservice teachers primarily used Chat GPT in lesson preparation, including plan creation, structuring and study of contents, and the investigation of misconceptions. They also explored real-life physics applications using Chat GPT. According to the preservice teachers, Chat GPT provides rich contents from diverse perspectives and real-time responses as well as predicts student questions and reactions. However, concerns were raised regarding the reliability of information and the potential of students to accept the knowledge provided by Chat GPT uncritically. Moreover, in this study, we discussed the use of generative AI in physics education.
Abstract : As the application of artificial intelligence (AI) gains popularity, its applications in various areas are actively explored. However, the introduction of AI to education in physics presents a challenge because of its many difficulties. To overcome these difficulties, we suggest an easy approach for square error analysis, which is the basis of machine learning programming theory that uses block coding techniques that have recently been widely used in elementary and secondary education. On this basis, the manner of introducing reinforced learning through simple game production can be presented. This study aims to contribute to the enhanced understanding required for the application of machine learning in physics research and education by helping students form the basis of understanding AI using the block coding method.
Abstract : Basis transformation between deeply bound molecular excited electronic states in the short in-ternuclear range with Hund’s case (a) and incoherent states dissociating into 2S + 2S ground state atoms with Hund’s case (e) in the presence of nuclear spin is successfully derived. Furthermore, transition amplitude between atomic scattering states with Hund’ case (e) and excited-bound hyperfine states with Hund’s case (a) are obtained. For illustration, a heteronuclear RbCs molecule is chosen and the basis transformation and calculation of transition amplitude performed.
Abstract : The conditions and mechanisms of the formation of self-organized patterns in a radiofrequency (RF) capacitively coupled plasma (CCP) are investigated using a two-dimensional particle-in-cell (PIC) simulation. Striation occurs in the direction parallel to the electrodes in an RF CCP via a novel physical mechanism, which is important to maintain the uniformity of CCPs used in semiconductor process equipment. We conducted a GPU-based parallelized PIC simulation to confirm the striations in two device structures and proposed methods for their control. We observed striations in asymmetric and symmetric structures. The size of striations is related to the electron energy relaxation length and ion collisional mean free path. Moreover, we provided insights into showerhead design by interpreting a case with a hole effect.
Abstract : The effect of supplying insufficient oxygen to patients with cerebrovascular disease must be verified. Changes in oxygen saturation (SpO2) and pulse waveforms measured by photoplethysmogram and Hall element clip-type pulsimeter were compared before/during/after hyperbaric oxygen therapy. At a maintained high pressure of 1.5 atm in the chamber, high-purity oxygen was flowed around the respirator of the subject at a flow rate of 5 L/min. The change in SpO2 reached 100% within 2 min. Given the increase in SpO2, cardiac muscle activity caused changes in systolic blood pressure, which resulted in a blood pressure increase of 16 mmHg. In particular, the heart rate decreased considerably from 68.8 beats/min to 48.8 beats/min, which implies the stabilization of heart motion caused by hyperbaric oxygen therapy. Diagnostic and treatment indicators can be created through daily-life management-type data collection and processing analysis through the regular monitoring of pulse waveforms in patients with cerebrovascular diseases and who require hyperbaric oxygen therapy.
Abstract : Anti-CD3e mAb (145-2C11), which is an immunotherapeutic antibody that inhibits the overactivation of T cells and the cause of the cytokine storm in COVID-19, was conjugated to the surface of magnetic nanoparticles (MNPs), and its magnetic properties were investigated. Glutaraldehyde was used as a cross-linking agent to conjugate MNPs and CD3 antibody (MNP-mAb). In the transmission electron microscopy–energy dispersive spectroscopy spectrum analysis, the order of the weights of the elements present was C > O > Fe > P > Cl > N > S. From the magnetoresistance curve of the phosphate-buffered saline solution containing the MNP-mAb conjugate measured in a two-terminal copper electrode bath, the magnetoresistance value, ratio, and solution coercivity were 18 MΩ, −22.2%, and 300 Oe, respectively, with symmetrical peaks. These results reveal that the antibody-conjugated MNPs can be regulated and induced to the desired target using an external magnetic field.
Abstract : The nonlinear evolution of large scale structures (LSSs) can disclose key cosmological information for understanding the physics beyond the standard model. In recent years, the use of deep neural networks in the direct extraction of cosmological information from LSS maps has gained increasing attention among research community. As the evolution of LSSs is governed by a growth factor that depends on contents of the universe combined with nonlinear effects, if neural networks can capture correlations at various epochs, then precision measurements of cosmological parameters can be improved. In this paper, we perform N-body simulations and demonstrate that image-based transformer networks configured for time-series data can be enhanced for the accurate extraction of Ωm and σ8 parameters.
Geun Taek YU, Geun Hyeong PARK, Eun Been LEE, Min Hyuk PARK*
New Phys.: Sae Mulli 2021; 71(11): 890-900
https://doi.org/10.3938/NPSM.71.890
Aekyung Shin, Donggeul Hyun, Jeongwoo Park
New Phys.: Sae Mulli 2023; 73(1): 37-43
https://doi.org/10.3938/NPSM.73.37
Chang Won AHN, Jin San CHOI, Muhammad SHEERAZ, Hwan Min KIM, Ill Won KIM, Tae Heon KIM*
New Phys.: Sae Mulli 2021; 71(12): 991-1003
https://doi.org/10.3938/NPSM.71.991
pISSN 0374-4914
