• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.15-35
• /
• 2010

Web service Technology has been developing rapidly as it provides a flexible application-to-application interaction mechanism. Several ongoing research efforts focus on various aspects of Web service technology, including the modeling, specification, discovery, composition and verification of Web services. The approaches advocated are often conflicting-based as they are differing expectations on the current status of Web services as well as differing models of their future evolution. One way of deciding the relative relevance of the various research directions is to look at their applicability to the currently available Web services. To this end, we conducted a survey on currently publicly available Web service repositories. Our aim is to get an idea of the number, complexity and composability of these Web services and see if this analysis provides useful information about the near-term fruitful research directions.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.473-482
• /
• 2021

Although several Hangul generation models using deep learning have been introduced, they require a lot of data, have a complex structure, requires considerable time and resources, and often fail in style conversion. This paper proposes a model CKFont using the components of the initial, middle, and final components of Hangul as a way to compensate for these problems. The CKFont model is an end-to-end Hangul generation model based on GAN, and it can generate all Hangul in various styles with 28 characters and components of first, middle, and final components of Hangul characters. By acquiring local style information from components, the information is more accurate than global information acquisition, and the result of style conversion improves as it can reduce information loss. This is a model that uses the minimum number of characters among known models, and it is an efficient model that reduces style conversion failures, has a concise structure, and saves time and resources. The concept using components can be used for various image transformations and compositing as well as transformations of other languages.

• Journal of KIISE:Computing Practices and Letters
• /
• v.7 no.2
• /
• pp.141-150
• /
• 2001

Manufacturing conb'ol applications consist of concurrent active components such as robots, AGV's (Automatic Guided Vehicles), and conveyors. Running of manufacturing control programs is interactions among those components. We can enhance the productivity and extendability of manufacturing control applications by using the object-oriented teclmology that models those components as reusable objects. But the objects in current object-oriented technology that encapsulate state and behavior infonnation are passive in a sense that those respond only when messages are sent to them. In this paper, we introduce the Distributed Active Object Systems (DAGS) approach that SUPPOltS active objects. Since active objects encapsulate control infonnation in addition to state and behavior information under COREA/Java-based distributed environment, they can represent manufacturing control components better than the objects in ordimuy object-oriented technology. TIus control infonnation provides an object with a featme that can monitor its own status as well as other object's status connected by intelface valiables. Active objects can initiate a behavior according to the change of those status. Therefore, we can sb-uctmally assemble self-initiating active objects by using intelface variables to construct a system without describing bow to control distributed objects by using message passing. As the DAOS approach supports object composability, we can enhal1ce the productivity and extendability of disbibuted manufactming control applications even better than the ordil1alY object-oriented approach. Also, the DAOS approach supports better component reusability with active objects that encapsulate control information .

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.2
• /
• pp.41-56
• /
• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.12
• /
• pp.499-508
• /
• 2022

A lot of research has been carried out on the Hangeul generation model using deep learning, and recently, research is being carried out how to minimize the number of characters input to generate one set of Hangul (Few-Shot Learning). In this paper, we propose a CKFont2 model using only 14 letters by analyzing and improving the CKFont (hereafter CKFont1) model using 28 letters. The CKFont2 model improves the performance of the CKFont1 model as a model that generates all Hangul using only 14 characters including 24 components (14 consonants and 10 vowels), where the CKFont1 model generates all Hangul by extracting 51 Hangul components from 28 characters. It uses the minimum number of characters for currently known models. From the basic consonants/vowels of Hangul, 27 components such as 5 double consonants, 11/11 compound consonants/vowels respectively are learned by deep learning and generated, and the generated 27 components are combined with 24 basic consonants/vowels. All Hangul characters are automatically generated from the combined 51 components. The superiority of the performance was verified by comparative analysis with results of the zi2zi, CKFont1, and MX-Font model. It is an efficient and effective model that has a simple structure and saves time and resources, and can be extended to Chinese, Thai, and Japanese.