• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.49-58
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• 2009

Top-down approach in the intelligent robot research has focused on the single object intelligence however, it has two weaknesses. One is that has a high cost and a long spending time of sensing, calculating and communications. The other is the difficulty of responding to react changes in the unpredictable environment. we propose the collective intelligence algorithm based on Bottom-up approach for improving these weaknesses and the applied agent model and verify by simulation. The Modified Flocking Algorithm proposed in this research is the algorithm which is modified version of the concept of the Flocking (Craig Reynolds) which is used to model the flocks, herds, and schools in the graphics or games, and simplified the operation of conventional Flocking algorithm to make it easy to apply for the number of group robots. We modeled the Boid agent and verified possibility collectivization of the Modified Flocking Algorithm by simulation. And We validated by the actual multiple mobile robot experiment.

• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.71-80
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• 2024

The Internet of Things (IoT) is an emerging element that is becoming increasingly indispensable to the Internet and shaping our current understanding of the future of the Internet. IoT continues to extend deeper into the daily lives of people, offering distributed and critical services. In contrast with current Internet, IoT depends on a dynamic architecture where physical objects with embedded sensors will communicate via cloud to send and analyze data [1-3]. Its security troubles will surely impinge all aspects of civilization. Mobile agents are widely used in the context of the IoT and due to the possibility of transmitting their execution status from one device to another in an IoT network, they offer many advantages such as reducing network load, encapsulating protocols, exceeding network latency, etc. Also, cryptographic technologies, like PKI and Blockchain technology, and Artificial Intelligence are growing rapidly allowing the addition of an approved security layer in many areas. Security issues related to mobile agent migration can be resolved with the use of these technologies, thus allowing increased reliability and credibility and ensure information collecting, sharing, and processing in IoT environments, while ensuring maximum autonomy by relying on the AI to allow the agent to choose the most secure and optimal path between the nodes of an IoT environment. This paper aims to present a new model to secure mobile agents in the context of the Internet of Things based on Public Key Infrastructure (PKI), Ethereum Blockchain Technology and Q-learning. The proposed model provides a secure migration of mobile agents to ensure security and protect the IoT application against malevolent nodes that could infiltrate these IoT systems.

• Knowledge Management Research
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• v.21 no.1
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• pp.175-195
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• 2020

The development of platform service based on the information and communication technology has revolutionized patterns of commercial transactions, driving the growth of global economy. Furthermore, the radical advancement of artificial intelligence(AI) presents the huge potential to innovate almost all the industrial and economic activities. Given these technological developments, the goal of this paper is to investigate AI's impact on the platform service innovation as well as its influence on the business performance. For the goal, this paper presents the review of the types of service innovation, the nature of platform services, and technological characteristics of leading AI technologies, such as chatbot and recommendation system. As an empirical study, this paper performs a multiple case study of Kakao Group which is the leading mobile platform service with the most advanced AI in Korea. To understand the role and effect of AI on Kakao platform service, this study investigated three cases, including chatbot agent of Kakao Bank, Smart Call service of Kakao Taxi, and music recommendation system of Kakao Mellon. The analysis results of the case study show that AI initiated innovations in platform service concepts, service delivery, and customer interface, all of which lead to a significant decrease in the transaction costs and the personalization of services. Finally, for the successful development of AI, this research emphasizes the significance of the accumulation of customer and operational data, the AI human capital, and the design of R&D organization.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.4
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• pp.407-413
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• 2006

Artificial aggregates made by coal fly ash that is classified as an industrial by-product was tested to oxidize hydrogen sulfide under various testing conditions. For the determination of optimum condition for converting coal fly ash to aggregates, specimens were prepared by varying ratio of fly ash, cement, water content, and foaming agent. These specimens were tested to determine specific gravity, water absorption, and compressive strength. Specimens, which were used for the removal of hydrogen sulfide, were selected based on the measured specific gravity, water absorption, and compressive strength. Tests for hydrogen sulfide removal were performed via batch and column tests. Under the testing conditions used in this study, removal rates of hydrogen sulfide were linearly proportional to amounts of coal fly ash, and further increased when water was added.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.9
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• pp.199-206
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• 2019

Experimental study on the durability characteristics to examine the feasibility of concrete with high water-tightness and self-healing performance to minimize maintenance of concrete for artificial ground is as follows. 1) When blending agent, swelling agents, and curing accelerator were added on the ternary system cement with blast-furnace slag fine particles and fly ash to give a self-healing property, higher blending strengths by 82% at design standard strength of 24MPa and by 74% at design strength of 30MPa, respectively could be obtained. 2) The permeability test for the specimens having high water-tightness and no shrinkage showed that the permeability was reduced at maximum of 98%. However, the permeability was decreased as the design strength was increased, showing the reduction rate of 87% at the design strength of 50MPa. 3) The depth of carbonation of blast-furnace slag and fly ash was increased in all the specimens compared with those of OPC only. However, as the material age was increased, carbonation penetration depth was decreased compared with the reference blend. 4) Compared with the reference blending using only OPC, the freeze-thaw resistance was higher in the case of blending with 40% of blast-furnace slag and 10% of fly ash at the design standard strength of 50MPa. In addition, the freeze-thaw resistance in general was superior in the design standard strength of 50MPa with the lower water-binder ratio (W/B) as compared with the design standard strength of 24MPa and 30MPa with the high water-binder ratios.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• Journal of the Korea Organic Resources Recycling Association
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• v.8 no.2
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• pp.140-145
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• 2000

This study was performed to investigate whether the earthworm cast could be reused as bulking agent in the whole processing of the food wastes using the earthworm. In addition, the growth conditions of microorganism lived upon earthworm lasts was investigated. Because the raw food wastes used in this experiment had low pH, and high moisture and organic matter contents, it was unsuitable to use as direct feeds to earthworm. However, when the food wastes were mixed with some earthworm cast, the mixtures were suitable to the feed condition and the growth environment of the earthworm. Therefore, it shows the possibility that the earthworm cast be reused as bulking agent for food wastes. In the microbiological investigation on earthworm cast, the bacteria showed most high density among the microbial species. And the microbial density showed higher under the mid-temperature than under high-temperature, and higher under the anaerobic than the aerobic condition. The drying methods of earthworm cast for the moisture adjusting, has no effect on microorganism growth whether natural or artificial drying. And the activity of enzyme presented more highly before the drying than after the drying.

• Reproductive and Developmental Biology
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• v.30 no.1
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• pp.1-5
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• 2006

Artificial activation of oocytes is a prerequisite for the successful cloning by nuclear transfer. This study investigated the effect of the different combination of activation agents such as electric pulse (E), thimerosal (Thi) + dithiothreitol (DTT), 6-dimethylaminopurine (6-DMAP) or cycloheximide (CH) on the developmental ability of porcine embryos derived from parthenogenetic activation (PA). PA embryos activated with chemicals showed significantly higher developmental rate to the blastocyst stage compared to the embryos activated with E alone ($21.5{\sim}28.1%$ vs. 18.0%, respectively). Of chemicals, Thi + DTT supported higher development to the blastoryst stage (28.1%). There was no significant difference in 1 pronucleus (PN) formation rate $(59.9{\sim}64.7%)$, but 2PN formation rate was significantly higher in PA embryos with additional activation using chemicals $(7.2{\sim}9.7%)$. In conclusion, this study shows that chemical activation after electric pulse can increase the development of porcine PA embryos.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.201-207
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• 2003

인터넷의 사용이 보편화됨에 따라 인터넷을 통한 정보 제공 서비스가 확대되고 있다. 이에 따라 빠르게 변화하는 사용자의 요구를 만족시킴과 동시에 편리하고 유용한 서비스를 제공하기 위하여 사용자와 자연스럽게 의사소통할 수 있는 대화형 에이전트의 연구가 활발히 진행되고 있다. 더불어 시스템의 효율적인 설계 또한 중요한 문제가 아닐 수 없다. 본 논문에서는 패턴매칭 기법과 베이지안 네트워크를 이용해 사용자 질의에 대한 적절한 답변을 생성하고, 스크립트 인터페이스를 통한 자동 스크립트 설계로 보다 효율적인 시스템 구축 방안을 제안해 보고자 한다. 실제 의류 사이트를 위한 안내 도우미 에이전트를 구현해 봄으로써 그 기능성을 평가해 본다.