Earticle

A luminescent porous silicon sensor, whose surface was passivated with organic molecule via hydrosilylation under various conditions, has been researched to measure the photoluminescence (PL) stability of porous silicon (PSi). Photoluminescent PSi were synthesized by an electrochemical etching of n-type silicon wafer under the illumination with a 300 W tungsten filament bulb during the etching process. The PL of PSi displayed at 650 nm, which is due to the quantum confinement of silicon quantum dots in the PSi. To stabilized the photoluminescence of PSi, the hydrosilylation of PSi with silole molecule containg vinyl group was performed. Surface morphologies of fresh PSi and surface-modified PSi were obtained with a cold FE-SEM. Optical characterization of red photoluminescent silicon quantum dots was investigated by UV-vis and fluorescence spectrometer.

To study the effects of hormones and neurotransmitters, zebrafish (Danio rerio) are a great substitute for water fleas (Daphnia). The zebrafish is an ideal vertebrate model because it has a transparent embryonic stage. It is easy to get consistent heart rate measurements in embryonic zebrafish when treating them with hormones and neurotransmitters. To observe the heart rate, two to three embryonic zebrafish are anesthetized with MS-222 and then transferred to a glass slide specifically designed for heart observation and easy application of various chemicals. After the heartbeats are counted for 2 minutes, apply either 100 μM epinephrine or 100 μM acetylcholine to the zebrafish. Wait 5, 10, and 20 minutes and count the heartbeats at each time point. All procedures are repeated three times. The final results are averaged and analyzed by using statistical methods. The above method which we have developed is practical enough for high school students to measure the heart rate in zebrafish under various conditions and to analyze the data set.

In this article, we will study which prime numbers are represented by the principal form. p = x2 + ny2. We will also give some results related to the form of primes of the form x2 + axy + y2.

Recently, due to global warming, the average temperature of the earth has risen, and the glaciers in the Antarctic and Arctic melt, leading to a rise in sea level, which is accompanied by powerful natural disasters such as strong typhoons and tsunamis around the world. Accordingly, a precipitation in summer in Korea also increased, and changes in the form of precipitation were showed with the increase. Compared to the past, the frequency of localized heavy rain is increasing, and the damage from flooding and flooding is increasing day by day. In this study, based on the precipitation data measured in hours from May to September from 2016 to 2021 according to the change in the precipitation form, according to the nature of the torrential rain investigated the change in the summer precipitation form. In addition, the trend of localized heavy rain from 2016 to 2021 was confirmed by classifying them into two types: localized heavy rains caused by cyclones and weather front, and by typhoons and large-scale cyclones. Through this, the change in precipitation due to the climate crisis should not be viewed as a single phenomenon, it should be reflected and discussed on our life focused on scientific and technological development, and it should be used as a stepping stone for realizing a humanistic.

We live in the age of artificial intelligence, and big data and artificial intelligence education are no longer just for majors, but are required to be able to handle non-majors as well. Software and artificial intelligence education for non-majors is not just a general education, it creates talents who can understand and utilize them, and the quality of education is increasingly important. Through such education, we can nurture creative talents who can create and use new values by fusion with various fields of computing technology. Since 2015, many universities have been implementing software-oriented colleges and AI-oriented colleges to foster software-oriented human resources. However, it is not easy to provide AI basic statistics education of big data analysis deception to nonmajors. Therefore, we would like to present a big data education model for non-majors in big data analysis so that big data analysis can be directly applied.

Collaborative filtering is one of the commonly used methods in the web recommendation system. Numerous researches on the collaborative filtering proposed the numbers of measures for enhancing the accuracy. This study suggests the movie recommendation system applied with Word2Vec and ensemble convolutional neural networks. First, user sentences and movie sentences are made from the user, movie, and rating information. Then, the user sentences and movie sentences are input into Word2Vec to figure out the user vector and movie vector. The user vector is input on the user convolutional model while the movie vector is input on the movie convolutional model. These user and movie convolutional models are connected to the fully-connected neural network model. Ultimately, the output layer of the fully-connected neural network model outputs the forecasts for user, movie, and rating. The test result showed that the system proposed in this study showed higher accuracy than the conventional cooperative filtering system and Word2Vec and deep neural network-based system suggested in the similar researches. The Word2Vec and deep neural network-based recommendation system is expected to help in enhancing the satisfaction while considering about the characteristics of users.

Recently, as a countermeasure for cyber breach attacks and confidential leak incidents on PC hard disk memory storage data of the metaverse industry, it is required when reviewing and developing a remote-based regular/realtime monitoring and analysis security system. The reason for this is that more than 90% of information security leaks occur on edge-end PCs, and tangible and intangible damage, such as an average of 1.20 billion won per metaverse industrial security secret leak (the most important facts and numerical statistics related to 2018 security, 10.2018. the same time as responding to the root of the occurrence of IT WORLD on the 16th, as it becomes the target of malicious code attacks that occur in areas such as the network system web due to interworking integration when building IT infrastructure, Deep-Access-based regular/real-time remote. The concept of memory analysis and audit system is key.

Under the two-phase warranty, the warranty period is divided into two intervals, one of which is for renewing replacement warranty, and the other is for minimal repair warranty. Jung[13] discusses the two types of extended two-phase warranty models. In this paper, we suggest the replacement model after the extended two-phase warranty that has been proposed by Jung[13]. To determine the optimal replacement policy, we adopt the expected cost rate per unit time. So, the expressions for the total expected cost, the expected length of the cycle and the expected cost rate per unit time from the user’s point of view are derived. Also, we discuss the optimal replacement policy and the uniqueness of the solution for the optimization. Furthermore, the numerical examples are provided to illustrate the proposed the replacement model.

최근 메타버스 산업체 pc 하드디스크 메모리 저장 데이타에 대한 사이버 침해 공격 및 기밀유출 사고대응 방안 으로 원격기반 상시 실시간 감시 및 분석 보안 체계를 검토 및 발전 시 요구된다. 이러한 사유는 정보보안 유출 90% 이상은 Edge단 pc에서 발생 되는 것으로 메타버스 산업보안기밀 유출 1건당 평균 10억 2,000만원 등의 유 형 및 무형 피해(2018보안과 관련된 가장 중요한 팩트와 수치통계 2018.10.16일 IT WORLD) 발생의 근본에 대 한 대응과 동시에 IT인프라 구축 시 연동 통합으로 네트웍 시스템 웹 등 영역에서 발생되는 악성코드 공격 대상 등의 대상이 되므로 이에 대한 대응책으로 Deep-Acess기반 상시 실시간 원격 메모리 분석 및 감사(audit)체계 개 념이 핵심이다.