• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.124-132
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• 2022

With growth in intelligence of mobile robots, interaction with humans is emerging as a very important issue for mobile robots and the pedestrian tracking technique following the designated person is adopted in many cases in a way that interacts with humans. Among the existing multi-object tracking techniques for pedestrian tracking, Simple Online and Realtime Tracking (SORT) is suitable for small mobile robots that require real-time processing while having limited computational performance. However, SORT fails to reflect changes in object detection values caused by the movement of the mobile robot, resulting in poor tracking performance. In order to solve this performance degradation, this paper proposes a more stable pedestrian tracking algorithm by correcting object tracking errors caused by robot movement in real time using wheel odometry information of a mobile robot and dynamically managing the survival period of the tracker that tracks the object. In addition, the experimental results show that the proposed methodology using data collected from actual mobile robots maintains real-time and has improved tracking accuracy with resistance to the movement of the mobile robot.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• Journal of the Korean institute of surface engineering
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• v.56 no.1
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• pp.40-54
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• 2023

In this work, we synthesized a novel electrochemical sensing materials based on tetracarboxylic copper phthalocyanine (TcCuPtc) conjugated PANI (TcCuPtc@PANI). The synthesized materials were employed to modify the screen-printed carbon electrode (SPCE) for the selective sensing of 4-nitrophenol. The TcCuPtc was conjugated with conducting polymer of PANI through the electrostatic interaction and π-π electron conjugation, the polymer film of PANI to inhibit the leakage of TcCuPtc from the surface of the electrode. The prepared TcCuPtc@PANI were characterized and confirmed by scanning electron microscopy (SEM) with EDX, ATR-IR, UV-vis absorption spectroscopy, cyclic voltammetry, and differential pulse voltammetry techniques. The prepared TcCuPtc@PANI/SPCE showed an excellent electrocatalytic sensing of 4-NP in the linear concentrations from 3 to 500 nM with a LOD of 0.03 nM and a sensitivity of 8.8294 ㎂/nM cm^-2. However, the prepared TcCuPtc@PANI/SPCE showed selective sensing of 4-NP in the presence of other interfering species. The practical applicability of the TcCuPtc@PANI/SPCE was employed for the sensing of 4-NP in different water samples by standard addition method and showed satisfactory recovery results.

• The Korean Journal of Food & Health Convergence
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• v.9 no.2
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• pp.1-6
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• 2023

As oil palm trees are an important economic source in many countries, particularly in Southeast Asia and Africa, the study of Ganoderma boninense is crucial for the sustainability of the oil palm industry. This study aims to understand the biology and ecology of the fungus, its pathogenesis, and the impact it has on oil palm trees. This knowledge can be used to develop management strategies to mitigate the damage caused by the fungus, such as the use of resistant varieties, chemical and biological control methods, and cultural practices. This study is to ensure the long-term productivity and sustainability of the oil palm industry. The main method of recent academic studies on this pathogen is molecular biology, with a focus on genetic analysis and functional genomics. Researchers have used techniques such as PCR, DNA sequencing, and transcriptomics to identify genes and pathways involved in pathogenesis and better understand the fungus's interactions with its host plant. Other methods used in recent studies include biochemical analysis, microscopy, and phytohormonal assays to investigate the biochemistry and physiology of the interaction between G. boninense and oil palm. This study is intended to provide implications from a new perspective by organizing and integrating studies on Ganoderma boninense.

• The Korean Journal of Food & Health Convergence
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• v.9 no.4
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• pp.19-23
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• 2023

The integration of ChatGPT, an AI-powered language model, is causing a profound transformation within the food industry, impacting various domains. It offers novel capabilities in recipe creation, personalized dining, menu development, food safety, customer service, and culinary education. ChatGPT's vast culinary dataset analysis aids chefs in pushing flavor boundaries through innovative ingredient combinations. Its personalization potential caters to dietary preferences and cultural nuances, democratizing culinary knowledge. It functions as a virtual mentor, empowering enthusiasts to experiment creatively. For personalized dining, ChatGPT's language understanding enables customer interaction, dish recommendations based on preferences. In menu development, data-driven insights identify culinary trends, guiding chefs in crafting menus aligned with evolving tastes. It suggests inventive ingredient pairings, fostering innovation and inclusivity. AI-driven data analysis contributes to quality control, ensuring consistent taste and texture. Food writing and marketing benefit from ChatGPT's content generation, adapting to diverse strategies and consumer preferences. AI-powered chatbots revolutionize customer service, improving ordering experiences, and post-purchase engagement. In culinary education, ChatGPT acts as a virtual mentor, guiding learners through techniques and history. In food safety, data analysis prevents contamination and ensures compliance. Overall, ChatGPT reshapes the industry by uniting AI's analytics with culinary expertise, enhancing innovation, inclusivity, and efficiency in gastronomy.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.64-72
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• 2023

This paper discusses the technical exploration of Ang Lee's cinematic works and the unique visual beauty he presents. Ang Lee has successfully tackled various themes and genres, creating films that harmoniously blend Eastern and Western cultural sensibilities. These films are technologically innovative and show the interaction between technology and art, industry and culture. Therefore, this paper analyses the correlation between film technology and visual beauty in Ang Lee's works, and explores the discourse on how the relationship between film technology and art has changed with the development of film. Furthermore, this paper aims to provide insights into how technological innovation can enhance artistic creativity. The contribution of this study lies in the in-depth exploration of the relationship between film technology and art, with a focus on technological innovation and the visual beauty in Ang Lee's works. The research findings reveal that Ang Lee's films showcase the application of advanced technologies, captivating audiences with their unique visual aesthetics. The utilization of emerging technologies enables his films to possess not only visual impact but also convey profound emotions and themes. We conclude that technological innovation in film not only provides artists with more creative tools and expressive techniques but also, when combined with artistic sensibilities, creates captivating and visually expressive cinematic works. This discovery offers a new perspective for film production and opens up greater possibilities for collaboration between artists and technology experts.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2419-2431
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• 2023

Experiments related to Boron Neutron Capture Therapy (BNCT) accomplished at the Institute of Nuclear Techniques (INT), Budapest University of Technology and Economics (TUB) are presented. Relevant investigations are required before designing BNCT for vivo applications. Samples of relevant boron compounds (H₃BO₃, BDTPA) usually employed in BNCT were investigated with neutron beam. Channel #5 in the research reactor (100 kW) of INT-TUB provides the neutron beam. Boron samples are mounted on a carrier for neutron irradiation. The particle attenuation of several carrier materials was investigated, and the one with the lowest attenuation was selected. The effects of boron compound type, mass, and compound phase state were also investigated. To detect the emitted charged particles, a traditional ZnS(Ag) detector was employed. The neutron beam's interaction with the detector-detecting layer is investigated. Graphite (as a moderator) was employed to change the neutron beam's characteristics. The fast neutron beam was also thermalized by placing a portable fast neutron source in a paraffin container and irradiating the H₃BO₃. The obtained results suggest that the direct measurement approach appears to be insufficiently sensitive for determining the radiation dose committed by the Alpha particles from the ¹⁰B (n,α) reaction. As a result, a new approach must be used.

• Journal of Smart Tourism
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• v.3 no.1
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• pp.41-47
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• 2023

Tourism and hospitality have encountered significant changes in recent years as a result of the rapid development of information technology (IT). Customers now expect more expedient services and customized travel experiences, which has intensified competition among service providers. To meet these demands, businesses have adopted sophisticated IT applications such as ChatGPT, which enables real-time interaction with consumers and provides recommendations based on their preferences. This paper focuses on the AI support-prompt middleware system, which functions as a mediator between generative AI and human users, and discusses two operational rules associated with it. The first rule is the Information Processing Rule, which requires the middleware system to determine appropriate responses based on the context of the conversation using techniques for natural language processing. The second rule is the Information Presentation Rule, which requires the middleware system to choose an appropriate language style and conversational attitude based on the gravity of the topic or the conversational context. These rules are essential for guaranteeing that the middleware system can fathom user intent and respond appropriately in various conversational contexts. This study contributes to the planning and analysis of service design by deriving design rules for middleware systems to incorporate artificial intelligence into tourism services. By comprehending the operation of AI support-prompt middleware systems, service providers can design more effective and efficient AI-driven tourism services, thereby improving the customer experience and obtaining a market advantage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2505-2528
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• 2023

The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.

• Advances in nano research
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• v.16 no.4
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• pp.353-363
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• 2024

The incorporation of nanoplatelets in composite and polymeric materials represents a recent and innovative approach, holding substantial promise for diverse property enhancements. This study focuses on the application of nanocomposites in the production of sports equipment, particularly soccer balls, aiming to bridge the gap between theoretical advancements and practical implications. Addressing the longstanding challenge of suboptimal interaction between carbon nanofillers and epoxy resin in epoxy composites, this research pioneers inventive solutions. Furthermore, the investigation extends into unexplored territory, examining the integration of glass fiber/epoxy composites with nanoparticles. The incorporation of nanomaterials, specifically expanded graphite and graphene, at a concentration of 25.0% by weight in both the epoxy structure and the composite with glass fibers demonstrates a marked increase in impact resistance compared to their nanomaterial-free counterparts. The research transcends laboratory experiments to explore the practical applications of nanocomposites in the design and production of sports equipment, with a particular emphasis on soccer balls. Analytical techniques such as infrared spectroscopy and scanning electron microscopy are employed to scrutinize the surface chemical structure and morphology of the epoxy nanocomposites. Additionally, an in-depth examination of the thermal, mechanical, viscoelastic, and conductive properties of these materials is conducted. Noteworthy findings include the efficacy of surface modification of carbon nanotubes in preventing accumulation and enhancing their distribution within the epoxy matrix. This optimization results in improved interfacial interactions, heightened thermal stability, superior mechanical properties, and enhanced electrical conductivity in the nanocomposite.