• Journal of KIISE:Computing Practices and Letters
• /
• v.6 no.2
• /
• pp.225-233
• /
• 2000

Local Number Portability (LNP), an Intelligent Network (IN) service, provides the ability to retain existing telephone numbers when switching from one telecommunications carrier to another, from one region to another, or from one service to another. Local Number Portability (LNP), an Intelligent Network (IN) service, provides the ability to retain existing telephone numbers when switching from one telecommunications carrier to another, from one region to another, or from one service to another. LNP is a key service for increasing competition in the local telephone marketplace. Many countries are now establishing detailed rules for ensuring competition between network operators. Because many major carriers will deploy their own LNP databases, a single access point must be provided to effectively manage and distribute updates to the common regional LNP database. This is called Number Portability Administration Center (NPAC). Recently, CORBA is being accepted as one of the key technologies for developing distributed application systems. To use CORBA for managing IN services, several standard organizations are working towards the integration of IN, TMN and CORBA. In this paper, we present our work on applying the TMN and CORBA technology for the service management of LNP. We first propose a CORBA-based LNP service management system architecture, We then present the design and implementation of a LNP service management system using CORBA.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.8
• /
• pp.359-368
• /
• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.208-212
• /
• 2001

This paper is for the optimized management of the knowledge abstracted from the World-Wide Web(WWW) in which we assume the infinite knowledge-base. Though we can abstract various useful knowledge such as the facts and the rules from the WWW pages, they may include many noisy knowledge. Therefore we have to reasonably reject them from the knowledge-base which is composed of knowledge abstracted from the WWW. To do this, we propose the oblivious memorization concept. This concept is characterized by the memorization based on the oblivion mechanism of human being. We assume the memorization is the function of the concern for any knowledge, oblivion ability and time. That is, the more concern for my knowledge the ore memorizable. And, the more oblivious and the more tine spent the less memorizable by exponentially. Where, tie assume the oblivion is the function of the degree of previous memorization, memorization ability md the number of knowledge stimulation. That is, the more previously memorized, the greater memorizing ability and the more frequently stimulated by any knowledge the less knowledge oblivious.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.4
• /
• pp.423-429
• /
• 2006

The systems in the ubiquitous computing environment need to provide users with context-aware services, intelligently interacting with the surrounding environment. Therefore, the systems in the ubiquitous computing environment require context-awareness ability in order to gather and analyze context information in various situations and environments. However, existing context-aware systems lack the ability to systematically generate and handle various types of context information, and only a few systems have ability learning from environment. In this paper, a general context model is defined to describe various contexts and a context-awareness framework is implemented based in the model, which makes it straightforward to handle and generate various types of context from diverse sensor. The framework is designed to allow a system to sensed, combined, inferred, and learned context information, in order to provide users with services in dynamic environments. We have implemented the proposed framework and applied it to a u-Health management system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.131-137
• /
• 2006

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new learning and evolution method based on reinforcement learning having delayed reward ability and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforcement learning having delayed reward is still useful even though when there is no immediate reward. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper. we verify the effectiveness of the proposed method by applying it to cooperative search problem.

• Journal of Information Science Theory and Practice
• /
• v.8 no.3
• /
• pp.30-46
• /
• 2020

This research aimed (1) to study and analyze the ability of current information retrieval (IR) systems based on views of information behavior (IB), and (2) to propose a conceptual framework for an IB model based on the collaboration between the system and user, with the intent of developing an IR system that can apply intelligent techniques to enhance system efficiency. The methods in this study consisted of (1) document analysis which included studying the characteristics and efficiencies of the current IR systems and studying the IB models in the digital environment, and (2) implementation of the Delphi technique through an indepth interview method with experts. The research results were presented in three main parts. First, the IB model was categorized into eight stages, different from traditional IB, in the digital environment, which can correspond to all behaviors and be applied to with an IR system. Second, insufficient functions and log file storage hinder the system from effectively understanding and accommodating user behavior in the digital environment. Last, the proposed conceptual framework illustrated that there are stages that can add intelligent techniques to the IR system based on the collaboration perspective between the user and system to boost the users' cognitive ability and make the IR system more user-friendly. Importantly, the conceptual framework for the IB model based on the collaboration perspective between the user and system for IR assisted the ability of information systems to learn, recognize, and comprehend human IB according to individual characteristics, leading to enhancement of interaction between the system and users.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.522-527
• /
• 2008

Socially Intelligent agent is the agent not only having the ability to recognize and to process human affect through learning and adaptation, but also having human-like social intelligence. By making human feel familiar with the computer, the agent is expected to enhance human-computer interaction (HCI) by providing users with the personalized services and interfaces. This paper proposes the framework for socially intelligent agents behaving socially according to the emotions recognized by ID3 algorithm and psychological OCC model. Also, the agent could process with the emotion to make socially intelligent response through three layered affect functioning model. Finally, the proposed agent can be applied for the development and application of socially intelligent agent in wide areas as the agent framework having similar affect and cognitive structure with human being.

• The KIPS Transactions:PartB
• /
• v.10B no.7
• /
• pp.795-802
• /
• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.16-21
• /
• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.6
• /
• pp.434-445
• /
• 2021

This paper proposes an optimal design method for an unmanned underwater vehicle (UUV) platform to overcome strong current. First, to minimize the hydrodynamic drag components in water, the vehicle is designed to have a streamlined disc shape, which help maintaining horizontal motion (zero roll and pitch angles posture) while overcoming external current. To this end, four vertical thrusters are symmetrically mounted outside of the platform to stabilize the vehicle's horizontal motion. In the horizontal plane, four horizontal thrusters are symmetrically mounted outside of the disc, and each of them has the same forward and reverse thrust performances. With these four thrusters, a specific thrust vector control (TVC) method is proposed, and for external current in any direction, four horizontal thrusters are controlled to generate a vectored thrust force to encounter the current while minimizing the vehicle's rotation and maintaining its heading. However, for the numerical simulations, the vehicle's hydrodynamic coefficients related to the horizontal plane are derived based on both theoretical and empirically derived formulas. In addition to the simulation, experimental studies in both the water tank and circulating water channel are performed to verify the vehicle's various final performances, including its ability to overcome strong current.