• Title/Summary/Keyword: industrial mathematics

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Distribution of Runs and Patterns in Four State Trials

  • Jungtaek Oh
    • Kyungpook Mathematical Journal
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    • v.64 no.2
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    • pp.287-301
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    • 2024
  • From the mathematical and statistical point of view, a segment of a DNA strand can be viewed as a sequence of four-state (A, C, G, T) trials. Herein, we consider the distributions of runs and patterns related to the run lengths of multi-state sequences, especially for four states (A, B, C, D). Let X1, X2, . . . be a sequence of four state independent and identically distributed trials taking values in the set 𝒢 = {A, B, C, D}. In this study, we obtain exact formulas for the probability distribution function for the discrete distribution of runs of B's of order k. We obtain longest run statistics, shortest run statistics, and determine the distributions of waiting times and run lengths.

Study on Geomatric Level of Vocational High School Students Based on the Van Hiele Theory (Van- Hiele 이론에 의한 실업계 고등학생들의 기하 수준 고찰)

  • 정영철
    • Journal of the Korean School Mathematics Society
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    • v.1 no.1
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    • pp.175-184
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    • 1998
  • The purpose of this study is that the Van Hiele theory can be applied to even vocational high school students. Through the comparison of Van Hiele level distribution of middle school students and high school students, it is that the aims of this study is to study the geomatric level of vocational high school students and to analize them, even so it can be to find for them the effective method of Geomatric education The subject of study is three kinds of vocational high school - commercial high school, industrial high school, fisheries high school - boys (240), girls (120) in Boryeong city, Chungchong Nam Do. We referred to Kim Mi-cheong′ thesis(1994) and Cheong Yean-sok′s thesis(1992) and compared my result with them. The method and the process of the study were based on the th method of CDASSG project. And we used Van Hiele Level Test as an instrument of measurement. We got the following conclusion as the result of the study 1. The 86% of the subject of the study was applied to the theory of Van Hiele - "Any students can reach level n just through level n-1." Even so the propriety of the theory proved to be from this study again. 2. The 88% of the subject of the study is applicable to below level 2. So if the proof is introduced to them in the class, it was very difficult for them to understand it. 3. The geometric level of vocational high school students is the same as the second grade of middle school. But we think to be desirable that a basic concept puts first in importance through recomposed teaching materials, because 68% of the students is seldom changed at level 1.

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Numerical and statistical analysis of Newtonian/non-Newtonian traits of MoS2-C2H6O2 nanofluids with variable fluid properties

  • Manoj C Kumar;Jasmine A Benazir
    • Advances in nano research
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    • v.16 no.4
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    • pp.341-352
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    • 2024
  • This study investigates the heat and mass transfer characteristics of a MoS2 nanoparticle suspension in ethylene glycol over a porous stretching sheet. MoS2 nanoparticles are known for their exceptional thermal and chemical stability which makes it convenient for enhancing the energy and mass transport properties of base fluids. Ethylene glycol, a common coolant in various industrial applications is utilized as the suspending medium due to its superior heat transfer properties. The effects of variable thermal conductivity, variable mass diffusivity, thermal radiation and thermophoresis which are crucial parameters in affecting the transport phenomena of nanofluids are taken into consideration. The governing partial differential equations representing the conservation of momentum, energy, and concentration are reduced to a set of nonlinear ordinary differential equations using appropriate similarity transformations. R software and MATLAB-bvp5c are used to compute the solutions. The impact of key parameters, including the nanoparticle volume fraction, magnetic field, Prandtl number, and thermophoresis parameter on the flow, heat and mass transfer rates is systematically examined. The study reveals that the presence of MoS2 nanoparticles curbs the friction between the fluid and the solid boundary. Moreover, the variable thermal conductivity controls the rate of heat transfer and variable mass diffusivity regulates the rate of mass transfer. The numerical and statistical results computed are mutually justified via tables. The results obtained from this investigation provide valuable insights into the design and optimization of systems involving nanofluid-based heat and mass transfer processes, such as solar collectors, chemical reactors, and heat exchangers. Furthermore, the findings contribute to a deeper understanding of stretching sheet systems, such as in manufacturing processes involving continuous casting or polymer film production. The incorporation of MoS2-C2H6O2 nanofluids can potentially optimize temperature distribution and fluid dynamics.

Data Mining based Forest Fires Prediction Models using Meteorological Data (기상 데이터를 이용한 데이터 마이닝 기반의 산불 예측 모델)

  • Kim, Sam-Keun;Ahn, Jae-Geun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.8
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    • pp.521-529
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    • 2020
  • Forest fires are one of the most important environmental risks that have adverse effects on many aspects of life, such as the economy, environment, and health. The early detection, quick prediction, and rapid response of forest fires can play an essential role in saving property and life from forest fire risks. For the rapid discovery of forest fires, there is a method using meteorological data obtained from local sensors installed in each area by the Meteorological Agency. Meteorological conditions (e.g., temperature, wind) influence forest fires. This study evaluated a Data Mining (DM) approach to predict the burned area of forest fires. Five DM models, e.g., Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Decision Tree (DT), Random Forests (RF), and Deep Neural Network (DNN), and four feature selection setups (using spatial, temporal, and weather attributes), were tested on recent real-world data collected from Gyeonggi-do area over the last five years. As a result of the experiment, a DNN model using only meteorological data showed the best performance. The proposed model was more effective in predicting the burned area of small forest fires, which are more frequent. This knowledge derived from the proposed prediction model is particularly useful for improving firefighting resource management.

Basic Research on Lighting Design for Learning Effect (학습효과 증진을 위한 조명설계에 대한 기초연구)

  • Lee, Boong-Joo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.4
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    • pp.518-524
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    • 2020
  • This study conducted basic research on an LED lighting design to improve the learning effect from brain wave analysis. The ideal environments of mathematics, language, and creative region can be different. Inside the space where the lighting environment can be experienced directly, the test subject consisted of common elements. Other lighting was blocked completely in controlled lighting conditions. The brain waves were analyzed according to the change in color temperature and illumination. The analyzer used was fabricated by EMOTIV Company. In the variable RGB LED light, the color of the light was measured, and the brain wave of each subject was determined. LED lights have variable color temperature (3000 [K], 4500 [K]. 250 [lux], 70% -350 [lux], 100% -500 [lux]). As research results, the highest concentration in a mathematics study was in the general condition of a high color temperature, in which the optimal condition was a 6000[K] color temperature and 350[lux] illumination. The optimal condition for a language study was a 4500[K] color temperature and 500[lux] illumination, and that of the creative study was 3000[K] color temperature and 500[lux] illumination. Overall, the possibility of emotional ability and concentrated learning efficiency can be improved by the LED lighting design with the color temperature and illumination.

Tomato Crop Diseases Classification Models Using Deep CNN-based Architectures (심층 CNN 기반 구조를 이용한 토마토 작물 병해충 분류 모델)

  • Kim, Sam-Keun;Ahn, Jae-Geun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.7-14
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    • 2021
  • Tomato crops are highly affected by tomato diseases, and if not prevented, a disease can cause severe losses for the agricultural economy. Therefore, there is a need for a system that quickly and accurately diagnoses various tomato diseases. In this paper, we propose a system that classifies nine diseases as well as healthy tomato plants by applying various pretrained deep learning-based CNN models trained on an ImageNet dataset. The tomato leaf image dataset obtained from PlantVillage is provided as input to ResNet, Xception, and DenseNet, which have deep learning-based CNN architectures. The proposed models were constructed by adding a top-level classifier to the basic CNN model, and they were trained by applying a 5-fold cross-validation strategy. All three of the proposed models were trained in two stages: transfer learning (which freezes the layers of the basic CNN model and then trains only the top-level classifiers), and fine-tuned learning (which sets the learning rate to a very small number and trains after unfreezing basic CNN layers). SGD, RMSprop, and Adam were applied as optimization algorithms. The experimental results show that the DenseNet CNN model to which the RMSprop algorithm was applied output the best results, with 98.63% accuracy.

Trend Analysis of Corona Virus(COVID-19) based on Social Media (소셜미디어에 나타난 코로나 바이러스(COVID-19) 인식 분석)

  • Yoon, Sanghoo;Jung, Sangyun;Kim, Young A
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.317-324
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    • 2021
  • This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.

Effect of Design for Interactive Narrative App, a Mobile App for Children's Education, on Enhancement of Learning Immersion and Intention to Continue Use (어린이 교육용 모바일 앱 인터랙티브 내러티브 디자인이 학습몰입도 증진, 지속사용의도에 미치는 영향)

  • Qing, Guo;Han, Hyun-Suk
    • Journal of Industrial Convergence
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    • v.20 no.10
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    • pp.157-167
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    • 2022
  • The purpose of this study is to verify the educational effectiveness of interaction design in mobile APP by observing the impact of interaction design for elementary school education on enhancing learning immersion and continuous use intention, and propose an interaction design scheme based on elementary school education APP. The research methods are literature research and questionnaire survey. Specifically, through the literature research method, the concepts and prior studies on the concept, reviews the continuous use intention and previous research of interaction design. Then, conducts a questionnaire survey on elementary school students in South Korea and China to understand the interaction design, learning immersion, and continuous use intention, and analyzes the relationship between variables.The research result of this study is to observe the influence of interaction design elements within interaction on learning immersion and continuous use intention with elementary school students who are users of elementary school education application as the objects. The results show that interaction design within interaction has a positive impact on improving learning immersion and continuous use intention. It can be thought that this is because in mathematics/science education, it is easy to understand theoretical concepts or explanations, and stories and images will be continued at each stage to help students learn without being bored.In conclusion, this study can confirm that interactive inline design has a positive effect of enabling learners to engage in learning and continue to use.

Estimation for the Variation of the Concentration of Greenhouse Gases with Modified Shannon Entropy (변형된 샤논 엔트로피식을 이용한 온실가스 농도변화량 예측)

  • Kim, Sang-Mok;Lee, Do-Haeng;Choi, Eol;Koh, Mi-Sol;Yang, Jae-Kyu
    • Journal of Environmental Science International
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    • v.22 no.11
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    • pp.1473-1479
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    • 2013
  • Entropy is a measure of disorder or uncertainty. This terminology is qualitatively used in the understanding of its correlation to pollution in the environmental area. In this research, three different entropies were defined and characterized in order to quantify the qualitative entropy previously used in the environmental science. We are dealing with newly defined distinct entropies $E_1$, $E_2$, and $E_3$ originated from Shannon entropy in the information theory, reflecting concentration of three major green house gases $CO_2$, $N_2O$ and $CH_4$ represented as the probability variables. First, $E_1$ is to evaluate the total amount of entropy from concentration difference of each green house gas with respect to three periods, due to industrial revolution, post-industrial revolution, and information revolution, respectively. Next, $E_2$ is to evaluate the entropy reflecting the increasing of the logarithm base along with the accumulated time unit. Lastly, $E_3$ is to evaluate the entropy with a fixed logarithm base by 2 depending on the time. Analytical results are as follows. $E_1$ shows the degree of prediction reliability with respect to variation of green house gases. As $E_1$ increased, the concentration variation becomes stabilized, so that it follows from linear correlation. $E_2$ is a valid indicator for the mutual comparison of those green house gases. Although $E_3$ locally varies within specific periods, it eventually follows a logarithmic curve like a similar pattern observed in thermodynamic entropy.

A Development of Infant Education Content for Animal Study (동물모형 학습을 위한 유아교육 콘텐츠 개발)

  • Lee, Kwang-Hyoung;Kim, Jung-Jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.9
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    • pp.3510-3516
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    • 2010
  • In this paper to make young children to learn habits of the animals, crying, features, and English and Korean language, The system was developed to target the zoo various animals exist. If young child places a doll on the front of interesting animal, then young child can learn to look through the display connected to the model. The zoo is reducing the current appearance of the zoo, sensors that can recognize animals are attached to each cage. Attached to each sensor has a unique ID, If this approach recognizes a doll baby and will transmit a unique ID to the handler. Transmitted ID search the matched value sent from the database to retrieve the content and then the content is to be output through the output device. Also if the doll near the animal's room, young children find out animal sound and basic learning by multimedia effects. At the same time Korean, English, Mathematics are learned.