• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.65-70
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• 2023

The "information roadway" will give us an impact of new PC based assignments and administrations, yet the unusualness of this new condition will ask for another style of human-PC association, where the PC transforms into a sharp, dynamic and customized partner. Interface administrators are PC programs that use Artificial Intelligence frameworks to give dynamic help to a customer with PC based errands. Operators drastically change the present client encounter, through the similitude that a specialist can go about as an individual collaborator. The operator procures its capability by gaining from the client and from specialists helping different clients. A couple of model administrators have been gathered using this methodology, including authorities that give customized help with meeting planning, electronic mail taking care of, Smart Personal Assistant and choice of diversion. Operators help clients in a scope of various ways: they perform assignments for the client's sake; they can prepare or educate the client, they enable diverse clients to work together and they screen occasions and methods.

• Journal of Advanced Navigation Technology
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• 제27권5호
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• pp.635-642
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• 2023

With the development of artificial intelligence technology, drones are evolving beyond simple remote control tools into intelligent drones that perform missions autonomously. The importance of drones is gradually gaining attention due to the use of drones in overseas military conflicts and the analysis of the future operational environment in Korea. AMAD is proposed for the rapid development of intelligent drones. In order to develop intelligent software based on AMAD, an integrated development environment (IDE) that supports users with functions such as debugging, performance evaluation, and monitoring is essential. In this paper, we define the concepts of the development environment required for intelligent software development and describe the results of reflecting them in the design of the IDE and AMAD's agents, SVI and MPD, which are interfaced with the IDE.

• The KIPS Transactions:PartB
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• 제12B권4호
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• pp.413-420
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• 2005

In this paper, we apply software agents, which use fuzzy logic and make autonomous decisions according to state transitions, to car driving environment. We carry out an experiment on artificial intelligent car driving in terms of real-time reactive agents. Inference techniques for constructing real-time reactive agents consider the settings with max-product inference, n-fuzzy rules, and n-associatives ($A_l,\;B_l),\;{\ldots}(A_n,\;B_n$). Then we perform defuzzification processes, extract a central value, and work out inference processes.

• Journal of Korea Multimedia Society
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• 제25권8호
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• pp.1156-1166
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• 2022

In this study, we examined voice shopping interaction in which consumers can be involved in the decision-making process. Sixteen kinds of voice shopping interaction were designed with differences in the existence of screen/product involvement/conversation style. Their effects on trust, cognitive load, satisfaction, and continuous intention to use were evaluated through a survey experiment. The main effect of conversation style was significant, and it was found that the more deeply involved users have higher trust. The interaction effect between conversation style and product involvement was also significant. Low involvement product buyers had the most positive user experience from the conversation style that included 'Ask for preference,' while high involvement product buyers had the most positive user experience from the conversation style that included both 'Ask for preference' and 'Question and Answer.' The main effect and interaction effect of the existence of screen was not significant. The results indicate that a positive user experience can be obtained when users are deeply involved in consumer decision-making, especially in purchasing high-involvement products.

• Journal of the Korean Society of Safety
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• 제19권1호
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• Journal of Korea Multimedia Society
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• 제11권1호
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• pp.76-87
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• 2008

As hardware performance rises, game users demand higher computer graphic, more convenient UI(User Interface), faster network, and smarter AI(Artificial Intelligence). At this time, however, AI development is accomplished by a co-development team or only one developer. For that reason, it's hard to verify that AI performance and basic game AI technology is lacking for developing high-level AI. Searching the merits and demerits of existing game AI platforms, we investigate main points to consider when designing game AI platforms in this paper. From this we suggest Darwin, a game platform, based on agent that developers embody AI easily and capable of proposing AI test with module that makes them find strategic position. And then evaluate achievement results through making agent used strategic module that Darwin offers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1053-1056
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• 2004

Research in Human Computer Interface (HCI) is towards development of an application environment able to deal with interactions of both human and computers that can be more intuitive and efficient. This can be achieved by bridging the gap between the synthetic virtual environment and the natural physical environment. Thus a project called Tangible Space Initiative (TSI) has been launched by KIST. TSI is subdivided into Tangible Interface (TI) which controls 3D cyber space with user's perspective, Responsive Cyber Space (RCS) which creates and controls the virtual environment and Tangible Agent (TA) which senses and acts upon the physical interface environment on behalf of any components of TSI or the user. This paper is a brief introduction to a new generation of Human Computer Interface that bring user to a new era of interaction with computers in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• Journal of the Korea Society for Simulation
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• 제18권4호
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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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 한국건설관리학회 2002년도 학술대회지
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• pp.180-187
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• 2002

Recently, there has been an increase in the demand to enhance the intelligence of construction equipment and systems. Especially for semiautonomous and autonomous systems that have great potential for impact on the construction industry, artificial intelligence approaches are required to generate instructions and plans necessary to perform tasks in dynamically changing environments on their own. The framework for an intelligent earthwork system (IES) is suggested in this paper. It generates a plan automatically for construction equipment and provides a means of cooperation between construction equipment seamlessly. This paper describes the system architecture, control strategy, task planning method, and resource allocation method for IES.