• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.285-294
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• 2006

The requirements of Computer Supported Cooperative Work supporting efficient cooperative or collaborative works between multi-users have been increasing in distributed environments. The various technical sections such as group communication technology and distributed processing technology should be provided in Cooperative Work. The replicated development of Cooperative Work applications of a number of common requirements increases development costs enormously and duplicated investment parts. Therefore, systematical development environments are required to develop these common requirements and applications efficiently in Cooperative Work applications development. In this study, we propose the hierarchical role-based coordination model that improves the coordination model of legacy mobile agent to be appropriate in Cooperative Work applications, and design the development environment for Cooperative Work applications based on mobile agent. The proposed hierarchical role-based coordination model provides multi-layered group concepts of mobile agent, and enables implementation of efficient coordination policy per group. Additionally, it supports efficient Cooperative Work application development by role assignment per group unit.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1035-1045
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• 2022

The purpose of this study is to examine whether spraying an anti-microbial agent into the slurry pit will reduce the noxious odor substances from piggery barns. For this, a total of 200 crossbred ([Landrace × Yorkshire] × Duroc) growing pigs with an initial average body weight (BW) of 23.58 ± 1.47 kg were selected and housed in two different rooms, i.e. control (CON) and treatment (TRT). Each room has 100 pigs (60 gilts and 40 borrows). For a period of 42 days, all pigs were fed with corn-soybean meal-based basal diet. Later the noxious odor substances were measured by the following methods. First, fecal samples were randomly collected and stored in sealed and unsealed containers, and sprayed with the non-anti-microbial agent (NAMA) (saline water) and multi-bacterial spraying (MBS) agent (200 :1, mixing ratio-fecal sample : probiotic), Second, the slurry pit of CON and TRT rooms were directly sprayed with NAMA and MBS, respectively. The fecal sample that was stored in sealed and un-sealed containers and sprayed with MBS significantly reduced NH₃ and CO₂ concentration at the end of day 7. However, at the end of day 42, the fecal sample showed a lower H₂S, methyl mercaptans, acetic acid, and CO₂ concentration compared to the unsealed container. Moreover, at the end of days 7, 14, 21, 28, 35, and 42 compared to the CON room and TRT room slurry pit emits lower concentrations of NH₃, acetic acid, H₂S, and methyl mercaptans, and CO₂ into the atmosphere. Based on the current findings, we infer that spraying anti-microbial agents on pig dung would be one of the better approaches to suppress the odor emission from the barn in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.311-314
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• 2002

The dynamic nature of the World Wide Web challenges Information Retrieval System to find information relevant and recent. Intelligent agents can complement the power of search engines to deal with this challenge. In this paper, we explain in manner of building Information Retrieval System based on intelligent agent technology. We present a tool called Websearcher. It was performed in Java environment. The object-oriented nature of Java and built-in facilities for multi-thread decreased our implementation effort. A modular software design makes it easy to configure the system for various experiments.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.503-506
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• 2006

In this paper, we suggest the Agent System for management and service of science and technology information that performs the collection, analyzing, processing and managing the information. Generally, any system can process the collection and service the information as usual method, but that mean can't be clear because of the data process method on different systems of hardware and software. So, it's very important point that the design and development of S&T information flow framework that can accept the various data, and we expect that the agent system adapted in framework guarantee the reduction of man power and process time and the enlarged system. Agent System consists of five multi agents, Resource Format Register Agent, Data Collector Agent, Data Analyzer Agent, Data Processor Agent and MetaDB Creator Agent. We describe the main roles and elements of agent systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.133-137
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• 2003

Various bioinformatics tools for biological data processing have been developed and most of them are available in public. Most bioinformatics works are carried out by a composite application of those tools. Several integration approaches have been proposed for easy use of the tools. This paper proposes a new multi agent system to integrate bioinformatics tools in the perspective of workflow since the composite applications of tools can be regarded as workflows. For the easy integration, the proposed system employs wrapper agents for existing tools, uses XML-based messages in the inter-agent communication, and agents are supposed to extract necessary information from the received messages. This allows new tools to be easily added on the integration framework. The proposed method allows various control structures in workflow definition and provides the progress monitoring capability of the on-going workflows. In particular, agents in this system have the rule-based architecture which allows the defined rule set to be a special role agent. This feature provides fast and flexible agent development to aid in managing the complexity of bioinformatics application. This system has been partially implemented and has been proven to be a viable implementation for workflow-based bioinformatics tool integration.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1256-1284
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• 2011

Although a existing consumer market have been studied in depth in the new technology product market, the market research on the overall level of value chain to consist of consumers, distributors, and manufacturers is weak. Therefore, in this paper consumers' purchase of new technology products were simulated and analyzed by a consumer selection model and a multi-agent model, which consist of consumers, distributors and manufacturers. Our research was focused on customer preference study in new technology product market by using conjoint analysis and discrete choice model. And changes in consumer behavior based on adoption of new technologies and offering of incentives were analyzed by ABM (Agent-based Model). In conclusion, the market share of technology products was risen when provision of incentives corresponding to inventory level and demand for new technology products occurred at the same time.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.121-144
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• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.

• ETRI Journal
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• v.37 no.2
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• pp.369-379
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• 2015

Fault management of virtualized network environments using user-driven network provisioning systems (NPSs) is crucial for guaranteeing seamless virtual network services irrespective of physical infrastructure impairment. The network service interface (NSI) of the Open Grid Forum reflects the need for a common standard management API for the reservation and provisioning of user-driven virtual circuits (VCs) across global networks. NSI-based NPSs (that is, network service agents) can be used to compose user-driven VCs for mission-critical applications in a dynamic multi-domain. In this article, we first attempt to outline the design issues and challenges faced when attempting to provide mission-critical applications using dynamic VCs with a protection that is both user-driven and trustworthy in a dynamic multi-domain environment, to motivate work in this area of research. We also survey representative works that address inter-domain VC protection and qualitatively evaluate them and current NSI against the issues and challenges.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.226-248
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• 2022

The existing model for sentiment analysis of product reviews learned from past data and new data was labeled based on training. But new data was never used by the existing system for making a decision. The proposed Aspect-based multi-agent Deep Reinforcement learning Sentiment Analysis (ADRSA) model learned from its very first data without the help of any training dataset and labeled a sentence with aspect category and sentiment polarity. It keeps on learning from the new data and updates its knowledge for improving its intelligence. The decision of the proposed system changed over time based on the new data. So, the accuracy of the sentiment analysis using deep reinforcement learning was improved over supervised learning and unsupervised learning methods. Hence, the sentiments of premium customers on a particular site can be explored to other customers effectively. A dynamic environment with a strong knowledge base can help the system to remember the sentences and usage State Action Reward State Action (SARSA) algorithm with Bidirectional Encoder Representations from Transformers (BERT) model improved the performance of the proposed system in terms of accuracy when compared to the state of art methods.