• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• Journal of Pharmacopuncture
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• v.26 no.1
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• pp.10-17
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• 2023

Objectives: Murraya paniculata (family-Rutaceae), popularly known as orange jasmine, is the most important evergreen plant. The Rutaceae family is economically significant due to its diverse edible fruits and essential oils. Methods: Murraya paniculata extracts (MPE) of leaf have been shown to include phenolic compounds, highly oxygenated flavonoids, flavanones, sesquiterpenoids, polymethoxy glycosides, and coumarins. Cyclocitral, methyl salicylate, trans-nerolidol, cubenol, isogermacrene, -cadinol, and cubeb-11-ene are all abundant in MPE. The usages of various parts of this plant, such as bark, leaves and flower, as a remedy for a variety of ailments as widely recorded in the traditional literature. The plant has anti-diabetic, anti-obesity, antibacterial, anti-implantation, anti-oxidative, cytotoxic, anti-diarrheal, antidepressant and anti-anxiety properties and many others. Results: The goal of the review is to reignite interest in this potential plant, encouraging researchers to continue their research in order to uncover novel therapeutic compounds for the treatment and management of a range of infections. The current review provided a comprehensive overview of this traditional unique plant. Conclusion: The review paves a way for exploring its active chemical elements with substantial pharmacological values further for potential benefits of mankind.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.245-251
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• 2023

Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.

• Journal of Korean Port Research
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• v.6 no.2
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• pp.43-64
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• 1992

This study discusses the interacting with deep water waves approaching from deep water based on the linear wave theory and steep sloping sea bottom floor by the numerical procedure. The results of particular interest are particle velocity and acceleration in x, y, z direction wave height amplification factor reflection coefficient and dimensionless pressure distribution on the steep sloping bottom with respect to the various incident wave angle. The wave loads relative to various bottom slopes, incident wave angles and wave periods on submerged breakwater and pipe are represented in comparison with mild sloping bottom the wave load parameters on the steep sloping bottom seemed to be influenced by variation of incident wave angle. In general the particle velocities and accelerations in x, y, z directions on the steep sloping bottom represented larger value or about two than those on the mild sloping bottom according to incident wave angle. However, the wave height amplification factors did not show distinct difference, but the slight variation with respect to the various incident angle showed on mild sloping bottom. The reflection coefficient increased with respect to increase of the incident angle on the steep sloping bottom the results also indicate that the very steep sloping beach produces a rather substantial amount of reflection as we expected. No significant variation of wave pressure was shown on the steep sloping bottom but it represented a certain amount of variation on the mild sloping bottom according to the various incident wave angle. The analysis at the OTEC site also showed similar results.

• Geomechanics and Engineering
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• v.35 no.4
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• pp.333-366
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• 2023

Rock as a mass generally exhibits discontinuities, commonly witnessed in rock slopes and underground structures like tunnels, rock pillars etc. When these discontinuities experiences loading, a new crack emerges from them which later propagates to a macro scale level of failure. The failure pattern is often influenced by the nature of discontinuity, geometry and loading conditions. The study of crack growth in rocks, namely its initiation and propagation, plays an important role in defining the true strength of rock and corresponding failure patterns. Many researchers have considered the length of the discontinuity to be fully persistent on rock or rock-like specimens by both experimental and numerical methods. However, only during recent decades, there has been a substantial growth in research interest with non-persistent discontinuities where the crack growth and its propagation phenomenon were found to be much more complex than persistent ones. The non-persistence fractures surface is generally considered to be open and closed. Compared to open flaws, there is a difference in crack growth behaviour in closed or narrow flaws due to the effect of surface closure between them. The present paper reviews the literature that has contributed towards studying the crack growth behaviour and its failure characteristics on both open and narrow flaws subjected to uniaxial and biaxial compression loading conditions.

• Korea Trade Review
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• v.46 no.6
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• pp.109-125
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• 2021

China has achieved remarkable economic growth through an extended period of rapid industrialization. However, adverse environmental issues have become more prevalent during this time of development. In particular, car exhaust emissions in the country have become one of the most substantial causes of environmental degradation in China. To combat these issues, the Chinese government is actively implementing green car policies to mitigate the negative environmental concerns. Likewise, Chinese consumers' interest in green cars has also increasing. Despite these changes in consumer perceptions, research on Chinese consumers' green consumption behavior is still in its infancy. Therefore, an empirical study was conducted to measure the relationship between zhongyong(中庸) values, new ecological paradigm(NEP), and green consumption behavior for 334 Chinese consumers. As a result, the study found that the three sub-dimensions of zhongyong(中庸) values(multi-dimensionality, flexibility and compatibility) and NEP had a significantly positive(+) effect on the purchase intention of green cars. It was also found that NEP positively mediates the effect of flexibility and harmony on purchase intention of green cars. This study is expected to provide academic outcomes on China, which is currently the world's fastest growing green car market, as well as providing practical strategic implications for establishing unique green marketing strategy for China.

• Journal of Dairy Science and Biotechnology
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• v.41 no.4
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• pp.163-178
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• 2023

The market size of functional health foods has experienced substantial growth driven by increasing consumer interest. In particular, the application of functional probiotics in various food products has resulted in consistent and progressive growth. One promising category is the application of probiotics in the manufacturing of cheese, which aligns with the rising demand for functional foods among consumers. The inherent advantages of cheese and probiotics provide consumers with a broad selection of functional foods. Therefore, it is crucial to identify functional probiotics that can withstand the cheese manufacturing process and exert significant effects on the flavor and taste of cheese. In this review, we discuss several strategies aimed at developing probiotic-supplemented cheeses for future dairy food markets.

• Food Science of Animal Resources
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• v.44 no.2
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• pp.255-268
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• 2024

Probiotic products have long been recognized for their health benefits. Additionally, milk has held a longstanding reputation as a dairy product that offers high-quality proteins and essential micronutrients. As awareness of the impact of food on health grows, interest in functional products such as probiotic dairy products is on the rise. Fermentation, a time-honored technique used to enhance nutritional value and food preservation, has been used for centuries to increase nutritional value and is one of the oldest food processing methods. Historically, fermented dairy products have been used as convenient vehicle for the consumption of probiotics. However, addressing the potential drawbacks of fermentation has recently led to increase in research on probiotic dairy drinks prepared without fermentation. These non-fermented dairy drinks have the advantage of maintaining the original flavors of milk drinks, containing potential health functional probiotics, and being an alternative dairy product that is helpful for probiotics intake. Currently, research on plant-based dairy products is rapidly increasing in the market. These developments might suggest the potential for novel forms of non-fermented dairy beverages with substantial prospects in the food market. This review aims to provide an overview of milk-based dairy beverages, both fermented and non-fermented, and discuss the potential of non-fermented dairy products. This exploration paves the way for innovative approaches to deliver probiotics and nutrition to consumers.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.93-104
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• 2024

This study conducts an in-depth analysis of user reviews from three leading metaverse platforms - Minecraft, Roblox, and Zepeto - using advanced topic modeling techniques to uncover key factors for business success. By examining a substantial dataset of user feedback, we identified and categorized the main themes and concerns expressed by users. Our analysis revealed that common issues across all platforms include technical functionality problems, user engagement and interest, payment concerns, and connection difficulties. Specifically, Minecraft users highlighted the importance of adventure and creativity, Roblox users expressed significant concerns about security and fraud, and Zepeto users focused heavily on the fairness of the in-game economy. The findings suggest that for metaverse platforms to achieve sustained success, they must prioritize the resolution of technical issues, enhance features that foster user engagement, ensure reliable connectivity, and address platform-specific concerns such as security for Roblox and payment fairness for Zepeto. These insights provide valuable guidance for developers and business strategists, emphasizing the need for robust technical infrastructure, engaging and diverse content, seamless user access, and transparent and fair economic systems. By addressing these key areas, metaverse platforms can improve user satisfaction, build a loyal user base, and secure long-term success in an increasingly competitive market.

• Journal of the Korean Society of Food Culture
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• v.25 no.3
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• pp.285-295
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• 2010

The purpose of this study was to compare the awareness of dietary patterns and health of full-time and employed housewives. The investigation gathered information on general characteristics, dietary lifestyle, nutritional status, and health by questionnaire as well as anthropometric measurements. The subjects included housewives living in Seoul and Gyeonggi Province (86 full-time and 127 working housewives) during November 2009 to January 2010. The average age, height, and weight of the housewives were $45.8{\pm}7.6\;yr$, $161.0{\pm}8.4\;cm$, and $55.7{\pm}6.3\;kg$, respectively. The average monthly income of the households was 3 million to 5 million won (31.4% full-time and 37.0% working housewives), and their average food expense was 200,000 to 500,000 won (46.5% full-time and 48.1% working housewives). More than 90% of the studied homes were nuclear families and the most common number of children was 2 to 3 (79.1% full-time and 76.4% working housewives). The ratio of employed housewives who ate regular meals was 35.4%, but that of the full-time housewives was 48.2% (p<0.05). Of the working housewives, 7.1% never ate breakfast and the primary reason for skipping breakfast was 'busy in the morning' (61.1%). The type of food that the housewives preferred when eating out was Korean food, both for the full-time and employed housewives (76.0%). All the housewives overate calories and the full-time housewives ate more protein, fat, vitamin A, vitamin B1, vitamin B6, niacin, vitamin C, vitamin E, folic acid, and cholesterol than the employed housewives (p<0.05). Both the full-time and employed housewives were more satisfied with supper than with other meals. About 30.6% of the full-time and 33.9% of the working housewives had no interest in health, but answered that regular exercise was very important for health (33.3% full-time and 39.7% working housewives). In conclusion, working housewives have poor dietary habits and nutrient intakes, thus substantial measures to improve these problems are urgently needed.