• Journal of Intelligence and Information Systems
• /
• v.14 no.1
• /
• pp.47-66
• /
• 2008

This study is aimed at proposing a new type of ubiquitous decision support system (u-DSS) portal which is embedded with two important mechanisms like an intelligent ontology management module (i-OMM) and multi-agent coordination mechanism (MACM). The proposed portal provides timely decision support to the involved decision entities (represented as agents) by taking advantage of the two mechanisms embedded on the portal. The most important virtue of the proposed portal is that it can resolve two problems such as semantic discordance and data confliction which are occurring very often in an ubiquitous computing environment. Frequent requests of revising the already established decision information due to the rapid changes in decision entities' requirements require the extremely flexible and intelligent u-DSS vehicle like theproposed mechanism. In this sense, the i-OMM is designed to provide support to solving the semantic discordance in the way that the i-OMM virtually integrates ontology view (IOV) to integrate heterogeneous ontology among the agents engaged inubiquitous commerce situations. Then the i-OMM sends the IOV to the MACM to resolve the conflicts among the involved agents. The proposed u-DSS portal was applied to the u-fulfillment problem in which all the involved decisionagents need their own requirements to be satisfied seamlessly and timely. The experimental results show that the proposed u-DSS portal is very robust and promising in the field of u-DSS and context modeling.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.469-481
• /
• 2018

DL (Deep Learning) is getting popular in various fields to implement artificial intelligence that resembles human learning and cognition. DL based on complicate structure of the ANN (Artificial Neural Network) requires computing power and computation cost. Variety of DL models with improved performance have been developed with powerful computer specification. The main purpose of this paper is to detect buildings from aerial images and evaluate performance of Mask R-CNN (Region-based Convolutional Neural Network) developed by FAIR (Facebook AI Research) team recently. Mask R-CNN is a R-CNN that is evaluated to be one of the best ANN models in terms of performance for semantic segmentation with pixel-level accuracy. The performance of the DL models is determined by training ability as well as architecture of the ANN. In this paper, we characteristics of the Mask R-CNN with various types of the images and evaluate possibility of the generalization which is the ultimate goal of the DL. As for future study, it is expected that reliability and generalization of DL will be improved by using a variety of spatial information data for training of the DL models.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.3
• /
• pp.141-148
• /
• 2021

This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.2
• /
• pp.143-157
• /
• 2008

Ubiquitous Web Services is able to be specified future Web Services technology for connecting with various application services in any device and network environments. The devices, in ubiquitous environment, have dynamic characteristic such as location and statuse. So, we must support methods of dynamic service discovery in ad-hoc network. There are many related works at transaction, security, QoS, semantic and Web Services composition with various fields. Recently, the studies are interested in the Ubiquitous by development of computing and network technology. However, they are an early stage. For this reason, in this paper, we propose a WSUN(Web Services on Universal Networks) for Ubiquitous Web Services. It is a SOA based framework. And this paper extracts necessity of WSUN environment from scenario. The framework is composed of US Broker(Universal Service Broker). It is designed for satisfying the conditions and supports dynamic service discovery using a US Registry (Universal Service Registry). Consequently. clients are able to discover and use Universal Service by protocol stack of the US Broker for Web Services. And it is a strong point which supports interoperability between heterogeneous networks.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.5
• /
• pp.49-58
• /
• 2005

There has been an increase in the interest of applications that use a combination of both pervasive computing technology and context-aware technology. This application based on the development environment along with the support of developing context-aware applications is now being researched thoroughly and by many. The service management system provides services that are needed for context-aware applications. This system is an integral part of the developmental environment of context-aware applications. But there is a restrictive matching based on ontology that uses simple syntactic matching or a plain type of service used in previous researches. And there is also no consideration for context-aware information. Also, if the user is unable to find a service that is satisfactory, or is a service which a user does not desire, they may use a service which is composed of other existing services. This paper proposes a service management system based on context-aware information. The proposed system enables the accurate finding of services by considering semantic matching methods based on ontology and context-aware information. If the user does not find a service that is helpful in the service registry, it can provide the service list to enable other existing service compositions, by providing the functionality of these service compositions. As a result, the experiment of the system proposed has shown that the system properly supported the service discovery based on context-aware information and service composition.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.6
• /
• pp.1069-1073
• /
• 2016

The Internet of Things (IoT) is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure. IoT is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine communications and covers a variety of protocols, domains, and applications. Key system-level features that IoT needs to support can be summarized as device heterogeneity, scalability, ubiquitous data exchange through proximity wireless technologies, energy optimized solutions, localization and tracking capabilities, self-organization capabilities, semantic interoperability and data management, embedded security and privacy-preserving mechanisms. Time information is a critical piece of infrastructure for any distributed system. Time information and time synchronization are also fundamental building blocks in the IoT. The IoT requires new paradigms for combining time and data. This paper reviews conventional time keeping mechanisms in the Internet and presents issues to be considered for combining time and data in the IoT.

• Journal of Internet Computing and Services
• /
• v.11 no.6
• /
• pp.123-133
• /
• 2010

XML has been become the new standard for publishing and exchanging data on the Web. However, most business data is still stored and maintained in relational database management systems. As such, there is an increasing need to efficiently publish relational data as XML data for Internet-based applications. The most important issue in the transformation is to reflect structural and semantic relations of RDB to XML schema exactly. Most transformation approaches have been done to resolve the issue, but those methods have several problems. In this paper, we discuss algorithm in transforming a relational database schema into corresponding XML schema in XML Schema. We aim to achieve not only explicit/implicit referential integrity relation information but also high level of nested structure while introducing no data redundancy for the transformed XML schema. To achieve these goals, we propose a transformation model which is redundancy free and then we improve the XML Schema structure by exploring more nested structure.

• KIISE Transactions on Computing Practices
• /
• v.22 no.10
• /
• pp.479-487
• /
• 2016

People can listen to almost every type of music by music streaming services without possessing music. Ironically it is difficult to choose what to listen to. A music recommendation system helps people in making a choice. However, existing recommendation systems have high computation complexity and do not consider context information. Emotion is one of the most important context information of music. Lyrics can be easily computed with various language processing techniques and can even be used to extract emotion of music from itself. We suggest a music-level similarity evaluation method using emotion and structure. Our result shows that it is important to consider semantic information when we evaluate similarity of music.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.12
• /
• pp.988-992
• /
• 2009

In this paper, we attempted to extract binary relations between terminologies using composite kernels consisting of convolution parse tree kernels and WordNet verb synset vector kernels which explain the semantic relationships between two entities in a sentence. In order to evaluate the performance of our system, we used three domain specific test collections. The experimental results demonstrate the superiority of our system in all the targeted collection. Especially, the increase in the effectiveness on KREC 2008, 8% in F1, shows that the core contexts around the entities play an important role in boosting the entire performance of relation extraction.

• KIISE Transactions on Computing Practices
• /
• v.21 no.6
• /
• pp.412-417
• /
• 2015

Context-sensitive spelling errors (CSSE) are hard to correct, since they are perfect words when analyzed alone. Determined only by considering the semantic and syntactic relations of their context, CSSEs affect largely the performance of spelling and grammar checkers. The existing Korean Spelling and Grammar Checker (KSGC 4.5) adopts a rule-based method, which uses hand-made correction rules for CSSEs. Using rule-based method, the KSGC 4.5 is designed to obtain the very high precision, which results in the extremely low recall. In this paper, we integrate our previous works that control the CSSE correction rules, in order to improve the recall without sacrificing the precision. In addition to the integration, facultative insertion of adverbs and conjugation suffix of predicates are also considered, as for constraint-loosening linguistic features.