• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1953-1972
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• 2022

The COVID-19 pandemic has resulted in a profound impact on large-scale gatherings throughout the world. Social distancing has become one of the most common measures to restrict the spread of the novel Coronavirus. Islamic pilgrimage attracts millions of pilgrims to Saudi Arabia annually. One of the mandatory rituals of pilgrimage is the symbolic stoning of the devil. Every pilgrim is required to perform this ritual within a specified time on three days of pilgrimage. This ritual is prone to congestion due to strict spatiotemporal requirements. We propose a pedestrian simulation model for implementing social distancing in the stoning ritual. An agent-based simulation is designed to analyze the impact of inter-queue and intra-queue spacing between adjacent pilgrims on the throughput and congestion during the stoning ritual. After analyzing several combinations of intra-queue and inter-queue spacings, we conclude that 25 queues with 1.5 meters of intra-queue spacing result in an optimal combination of throughput and congestion. The Ministry of Hajj in Saudi Arabia may benefit from these findings to manage and plan pilgrimage more effectively.

• Advances in concrete construction
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• v.14 no.2
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• pp.139-151
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• 2022

Filling materials poured into precast member joint are subjected to restraint stress by the precast member and joint reinforcement. The induced stress will likely cause cracks at early ages and performance degradation of the entire structure. To prevent these issues and design reasonable joints, it is very important to analyze and evaluate the restrained shrinkage cracks of filling materials at various restraint conditions. In this study, a new time zero-that defines the shrinkage development time of a filling material-is proposed to calculate the accurate amount of shrinkage. The tensile stresses and strengths at different ages were compared through the ring test (AASHTO PP34) to evaluate the crack potential of the restrained filling materials at various restraint conditions. The mixture which contained an expansive additive and a shrinkage reducing agent exhibited high resistance to shrinkage cracking owing to the high-drying shrinkage compensation effect. The high-performance, fiber-reinforced cement composite, and ultra-high-performance, fiber-reinforced cement composite yielded very high resistance to shrinkage and cracking owing to the pull-out property of steel fibers. To this end, multiple nonlinear regression analyses were conducted based on the test results. Accordingly, a modified tensile stress equation that considered both the geometric shape of the specimen and the intrinsic properties of the material is proposed.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.131-139
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• 2024

Crew Transfer Vessels (CTVs) are primarily used for the maintenance of offshore wind farms. Despite being manually operated by professional captains and crew, collisions with other ships and marine structures still occur. To prevent this, the introduction of autonomous navigation systems to CTVs is necessary. In this study, research on the obstacle avoidance system of the autonomous navigation system for CTVs was conducted. In particular, research on obstacle avoidance simulation for CTVs using deep reinforcement learning was carried out, taking into account the currents and wind loads in offshore wind farms. For this purpose, 3 degrees of freedom ship maneuvering modeling for CTVs considering the currents and wind loads in offshore wind farms was performed, and a simulation environment for offshore wind farms was implemented to train and test the deep reinforcement learning agent. Specifically, this study conducted research on obstacle avoidance maneuvers using MATD3 within deep reinforcement learning, and as a result, it was confirmed that the model, which underwent training over 10,000 episodes, could successfully avoid both static and moving obstacles. This confirms the conclusion that the application of the methods proposed in this study can successfully facilitate obstacle avoidance for autonomous navigation CTVs within offshore wind farms.

• 한국유가공학회:학술대회논문집
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• 2005.06a
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• pp.37-61
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• 2005

Microcapsules consisting of natural, biodegradable polymers for controlled and/or sustained core release applications are needed. Physicochemical properties of whey proteins suggest that they may be suitable wall materials in developing such microcapsules. The objectives of the research were to develop water-insoluble, whey protein-based microcapsules containing a model water-soluble drug using a chemical cross-linking agent, glutaraldehyde, and to investigate core release from these capsules at simulated physiological conditions. A model water soluble drug, theophylline, was suspended in whey protein isolate (WPI) solution. The suspension was dispersed in a mixture of dichloromethane and hexane containing 1% biomedical polyurethane. Protein matrices were cross-linked with 7.5-30 ml of glutaraldehyde-saturated toluene (GAST) for 1-3 hr. Microcapsules were harvested, washed, dried and analyzed for core retention, microstructure, and core release in enzyme-free simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) at 37$^{\circ}C$, A method consisting of double emulsification and heat gelation was also developed to prepare water-insoluble, whey protein-based microcapsules containing anhydrous milkfat (AMF) as a model apolar core. AMF was emulsified into WPI solution (15-30%, pH 4.5-7.2) at a proportion of 25-50% (w/w, on dry basis). The oil-in-water emulsion was then added and dispersed into corn oil (50 $^{\circ}C$)to form an O/W/O double emulsion and then heated at 85$^{\circ}C$ for 20 min for gelation of whey protein wall matrix. Effects of emulsion composition and pH on core retention, microstructure, and water-solubility of microcapsules were determined. Overall results suggest that whey proteins can be used in developing microcapsules for controlled and sustained core release applications.

• 한국균학회소식:학술대회논문집
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• 2014.10a
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• pp.11-11
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• 2014

Fungal pathogens have huge impact on health and economic wellbeing of human by causing life-threatening mycoses in immune-compromised patients or by destroying crop plants. A key determinant of fungal pathogenesis is their ability to undergo developmental change in response to host or environmental factors. Genetic pathways that regulate such morphological transitions and adaptation are therefore extensively studied during the last few decades. Given that epigenetic as well as genetic components play pivotal roles in development of plants and mammals, contribution of microbial epigenetic counterparts to this morphogenetic process is intriguing yet nearly unappreciated question to date. To bridge this gap in our knowledge, we set out to investigate histone modifications among epigenetic mechanisms that possibly regulate fungal adaptation and processes involved in pathogenesis of a model plant pathogenic fungus, Magnaporthe oryzae. M. oryzae is a causal agent of rice blast disease, which destroys 10 to 30% of the rice crop annually. Since the rice is the staple food for more than half of human population, the disease is a major threat to global food security. In addition to the socioeconomic impact of the disease it causes, the fungus is genetically tractable and can undergo well-defined morphological transitions including asexual spore production and appressorium (a specialized infection structure) formation in vitro, making it a model to study fungal development and pathogenicity. For functional and comparative analysis of histone modifications, a web-based database (dbHiMo) was constructed to archive and analyze histone modifying enzymes from eukaryotic species whose genome sequences are available. Histone modifying enzymes were identified applying a search pipeline built upon profile hidden Markov model (HMM) to proteomes. The database incorporates 22,169 histone-modifying enzymes identified from 342 species including 214 fungal, 33 plants, and 77 metazoan species. The dbHiMo provides users with web-based personalized data browsing and analysis tools, supporting comparative and evolutionary genomics. Based on the database entries, functional analysis of genes encoding histone acetyltransferases and histone demethylases is under way. Here I provide examples of such analyses that show how histone acetylation and methylation is implicated in regulating important aspects of fungal pathogenesis. Current analysis of histone modifying enzymes will be followed by ChIP-Seq and RNA-seq experiments to pinpoint the genes that are controlled by particular histone modifications. We anticipate that our work will provide not only the significant advances in our understanding of epigenetic mechanisms operating in microbial eukaryotes but also basis to expand our perspective on regulation of development in fungal pathogens.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.55-72
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• 2017

Autonomous Vehicles(AV) are considered as an alternative to solve various social problems. Many researches which are related to developing technologies and AV operations have been conducted vastly and on-going. However, there seem to be little studies on various influences of AI algorithm on driving installed in AV. This study aims to examine the impacts of the ethical decisions made by Utilitarianism-based AI in AV when the oncoming car crossed over the central line. It establishes scenarios about situation of encroaching a central line and analyzes traffic impacts of ethical decision made by AV. According to the results of the analyses, as th accident occurs, overall speed of traffic decrease. There is a negative impact on the traffic flow when AV made an Utilitarian-based ethical decision by changing the lane. However, when AV choose to collide head-on, there is a positive effect to relieve traffic flow with an assistance of CACC, equipped.

• Journal of Ginseng Research
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• v.39 no.4
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• pp.304-313
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• 2015

Background: Ginsenoside Rg3 is a promising anticancer agent. It is usually produced by heat treatment of ginseng, in which ginsenoside Rb1 is the major ginsenoside. A kinetic study was conducted to optimize ginsenoside Rg3 production by the heat treatment of ginsenoside Rb1. Methods: Ginsenoside Rb1 was heated using an isothermal machine at $80^{\circ}C$ and $100^{\circ}C$ and analyzed using HPLC. The kinetic parameters were calculated from the experimental results. The activation energy was estimated and used to simulate the process. The optimized parameters of ginsenoside Rg3 production are suggested based on the simulation. Results: The rate constants were $0.013h^{-1}$ and $0.073h^{-1}$ for the degradation of ginsenosides Rb1 and Rg3 at $80^{\circ}C$, respectively. The corresponding rate constants at $100^{\circ}C$ were $0.045h^{-1}$ and $0.155h^{-1}$. The estimated activation energies of degradation of ginsenosides Rb1 and Rg3 were 69.2 kJ/mol and 40.9 kJ/mol, respectively. The rate constants at different temperatures were evaluated using the estimated activation energies, and the kinetic profiles of ginsenosides Rb1 and Rg3 at each temperature were simulated based on the proposed kinetic model of consecutive reaction. The optimum strategies for producing ginsenoside Rg3 from ginsenoside Rb1 are suggested based on the simulation. With increased temperature, a high concentration of ginsenoside Rg3 is formed rapidly. However, the concentration decreases quickly after the reaching the maximal concentration value. Conclusion: The optimum temperature for producing ginsenoside Rg3 should be the highest temperature technically feasible below $180^{\circ}C$, in consideration of the cooling time. The optimum reaction time for heat treatment is 30 min.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.459-464
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• 2006

It has been well proved that shiphandling simulators are efficient and useful facilities for training and education of cadets and seafarers. Most of the maritime universities and many maritime training institutes all over the world have installed shiphandling simulators, which play important roles in maritime education and training. However, most of the Shiphandling simulators are standalone facilities with diversities on system architectures, layouts and functions. STCW78/95 requires simulators used for simulator-based training shall be suitable for the selected objectives and training tasks. To ensure the shiphandling simulator facilities meet the requirements of STCW convention and other expanded applications, collaborated research and coordination are needed in development and application of shiphandling simulators. Performance standard should be established for shiphandling simulator systems considering the advanced research needs as well as the needs in education, training, and assessment of competence. Standardizing and exchanging shiphandling mathematical models will improve critical performance of the system. Cooperated research on model course and training assessment approaches will enhance the training standard. In addition, the rapid spread of the internet technology has shown a promising future of application of shiphandling simulators through internet. Research has been carried out on internet based integration of multiple shiphandling simulators. A multi-agent based system, including necessary hardware, has been developed. Collaborated operation of the system can be of benefit in filling the gaps of the technical and operational level and methodology between maritime universities, enhancing mutual understanding of the navigation customs and culture background among cadets and seafarers from different countries, facilitating communication and maritime English training, and extending the functions of shiphandling simulators.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1153-1160
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• 2021

This paper proposes a routing algorithm that determines the optimal path using deep reinforcement learning in software-defined networks. The deep reinforcement learning model for learning is based on DQN, the inputs are the current network state, source, and destination nodes, and the output returns a list of routes from source to destination. The routing task is defined as a discrete control problem, and the quality of service parameters for routing consider delay, bandwidth, and loss rate. The routing agent classifies the appropriate service class according to the user's quality of service profile, and converts the service class that can be provided for each link from the current network state collected from the SDN. Based on this converted information, it learns to select a route that satisfies the required service level from the source to the destination. The simulation results indicated that if the proposed algorithm proceeds with a certain episode, the correct path is selected and the learning is successfully performed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.29-35
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• 2023

In this paper, we propose a SW-EDU bot, a chatbot learning model for coding education by using a chatbot system. The same scenario-based models are created on the basis of Dialogflow and Kakao i Open Builder, which are representative chatbot builders. And then a SW-EDU bot is designed and implemented by selecting the builder more appropriate to our purpose. The implemented chatbot system aims to learn effective learning methods while encouraging self-direction of users by providing learning type selection, concept learning, and problem solving by difficulty level. In order to compare the usability of chatbot builders, five indicators are selected, and based on these, a builder with a comparative advantage is selected, and SW-EDU bot is implemented based on these. Through usability evaluation, we analyze the feasibility of SW-EDU bot as a learning support tool and confirm the possibility of using it as a new coding education learning tool.