• Journal of Information Science Theory and Practice
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• v.12 no.4
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• pp.36-49
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• 2024

In recent years, the concept of a configurable process model has made many contributions, with the need for generic and reusable models. The high demand for this type of generic model is accompanied by quality requirements, as these models must be as comprehensive as possible to facilitate the task of customization. Many approaches exist to deal with configurable process models, especially in the field of process mining, including its three types of techniques: discovery, conformance, and enhancement. However, there is a lack of semantic representation in the resulting models. In this study, we propose a novel automated approach based on the extension of the Inductive Miner algorithm used to discover business process models. This method discovers a semantically annotated configurable process model using two ontologies: variability ontology and domain ontology-related concepts, which will improve and facilitate the configurable process model customization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9B
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• pp.760-773
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• 2003

The Internet is evolving from best-effort service toward an integrated or differentiated service framework with quality-of-service (QoS) assurances that are required for new multimedia service applications. Given this increasing demand for high bandwidth Internet with QoS assurances in the coming years, an IP/MPLS-based control plane combined. with a wavelength-routed dense-wavelength division multiplexing (DWDM) optical network is seen as a very promising approach for the realization of future re-configurable transport networks. This paper proposes a differentiated lambda establishment process for QoS guarantees based on the differentiated MPLS service (DMS) model. According to the QoS characteristics of wavelength in optical links and the type of used Optical Cross-Connect (OXC) nodes in DWDM next generation optical Internet backbone network, a differentiated wavelength assignment strategy that considers QoS recovery capability is also suggested.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1388-1400
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• 2000

An important technical issue in recent software development is to make needed software by the composition of components that are assemblable, and configurable, and independently extracted. The main advantage of component-based software development is reducing development time and cost. It is more cost-effective in development time to use components that are already developed than developing from scratch. There are two ways of component-based software development: one is to compose self-developed components, and the other is to by the components developed by third-parties and compose them. In the second case, existing non component programs must can be used for reuse in the component development. In this paper, we approach two methods for increase of reusability of Java program. First, we suggest the technique of extracting the elements suitable for the Beans component model from Java program, and then we show a process and a guideline of converting the extract elements into the Beans component model. Second, we suggest a technique of automatically extracting component information from the Java Beans component, expressing them in XML, its is possible to reuse the efficient component environment.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.267-277
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• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.