• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5877-5897
• /
• 2018

With the popularity of mobile networks and smartphones, geo-textual publish/subscribe messaging has attracted wide attention. Different from the traditional publish/subscribe format, geo-textual data is published and subscribed in the form of dynamic data flow in the mobile network. The difference creates more requirements for efficiency and flexibility. However, most of the existing Top-k geo-textual publish/subscribe schemes have the following deficiencies: (1) All publications have to be scored for each subscription, which is not efficient enough. (2) A user should take time to set a threshold for each subscription, which is not flexible enough. Therefore, we propose an efficient and flexible Top-k geo-textual publish/subscribe scheme. First, our scheme groups publish and subscribe based on text classification. Thus, only a few parts of related publications should be scored for each subscription, which significantly enhances efficiency. Second, our scheme proposes an adaptive publish/subscribe matching algorithm. The algorithm does not require the user to set a threshold. It can adaptively return Top-k results to the user for each subscription, which significantly enhances flexibility. Finally, theoretical analysis and experimental evaluation verify the efficiency and effectiveness of our scheme.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.4
• /
• pp.349-354
• /
• 2014

PIN(Personal Identification Number)-based identification method has been used to identify the user of smart cards. However, this type of identification method has several problems. Firstly, PIN can be forgotten by owners of the card. Secondly, PIN can be used by others illegally. Furthermore, the possibility of hacking PIN can be high because this PIN type matching process is performed on terminal. Thus, in this paper we suggest a new identification method which is performed on smart card using face feature information. The proposed identification method uses low-sized face feature vectors and simple matching algorithm in order to get around the limits in computing capability and memory size of smart card.

• Journal of Broadcast Engineering
• /
• v.18 no.1
• /
• pp.1-9
• /
• 2013

Accuracy of the 3-D model is essential in model-based camera tracking. However, 3-D object modeling requires dedicated and complicated procedures for precise modeling without any errors. Even if a 3-D model contains a certain level of errors, on the other hand, the tracking errors cause by the modeling errors can be different from its perceptual errors; thus, it is an important aspect that the camera tracking can be successful without precise 3-D modeling if the modeling errors are within the user's permissible range. In this paper, we analyze the tolerance of 3-D object modeling errors by comparing computational matching errors with perceptual matching errors through user evaluations, and also discuss permissible ranges of 3-D object modeling errors.

• Journal of Korea Game Society
• /
• v.16 no.3
• /
• pp.97-108
• /
• 2016

Multi-client online games usually employ multi-serve architectures. For group play, if the user response time deviation between the clients in a group is large, the fairness and attractions of the game will be degraded. In this paper, given new clients, we propose a method for assigning the clients to servers to minimize the deviation of client-server distance which plays a major role in the user response time. This method also supports client matching for group play and server load balancing. We formulate the client-server assignment problem as an IP one, and present a GA(Genetic Algorithm)-based algorithm to solve it. We experimented our method under various settings and analyzed its features. To our survey, little research has been previously performed on client-server assignment under consideration of client matching, distance deviation minimization and server load balancing.

• The KIPS Transactions:PartB
• /
• v.12B no.7 s.103
• /
• pp.803-810
• /
• 2005

Information retrieval is one of the most challenging areas in which the ontology technology is effectively used. Among them image retrieval using the image meta data and ontology is the one that can substitute the keyword-based image retrieval. In the paper, the retrieval of visual media such as the art image and photo picture is handled. It is assumed that there are more than one service providers of the visual media and also there is one central service broker that mediates the user's query. Given the user's query the first step that must be done in the service broker is to get the list of candidate service providers that fit the query. This is done by defining various ontologies such as the service ontology and matching the query against the ontology and providers. A novel matching method based on the ASN.1. The experiment shows that the method is more effective than existing tree-based and interval-based methods. Ontology merging issue is also handled that can happen when the service providers register their service into the service broker. An effective method is also proposed.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1067-1087
• /
• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.311-326
• /
• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.617-618
• /
• 2017

Recently, IoT can provide a service considering user's convenience by configuring the inside of the home as a smart environment. However, the existing system can not change the configuration of the home smart environment by the user, and there is a problem in compatibility between the server and the heterogeneous device. In this paper, we propose a system to reconfigure the relationship between the device and the server in the smart home environment to solve that. In a smart home environment, The user can add and delete devices through the application. In addition, when a new device is added, the server searches the schema for the device and establishes an automatic relationship. This makes it possible for the user to easily change the configuration of the smart home environment.

• Journal of Internet Computing and Services
• /
• v.15 no.5
• /
• pp.83-93
• /
• 2014

Providing personalized services customized to users' needs and preferences becomes highlighted as a key area of user-context computing. It is essential for context-aware technology to be developed more intelligent and meaningful services by being widely applied to a variety of sectors and domains. SDO (Standard Development Organization) such as MPEG and W3C has been actively developed to be standardized services and to improve context-awareness services. Yet current standards related to context-aware technology, such as MPEG-7, MPEG-21, MPEG-V, and emotionML, are not capable enough to support various systems and diverse services. Against this backdrop, the MPEG User Description, referred to also as MPEG-UD Standard, is to ensure interoperability among recommendation services, which take into account user's context when generating recommendations to users. In this light, we introduce standards related to the user context and propose the structure for RD-Engine and the Remote Responsive User Interface(RRUI) system in reference to MPEG-UD. This system collects unit resources matching specific condition according to the user's contexts described by MPEG-UD. In so doing, it improves adaptive user interface considering device features in real-time. By automatically generating adaptive user interfaces tailored to an individual's contexts, the proposed system aims to achieve high-quality user experience for a complex service.

• Journal of Digital Convergence
• /
• v.10 no.2
• /
• pp.293-297
• /
• 2012

In order to provide with personalized recommendation service in context-awareness environment, the collected context data should be analyzed fast and the objective of user should be able to inferred effectively. But, the context collected from the mobile devices is not suitable for applying the existing inference algorithms as they are due to the omission or uncertainty of information and the efficient algorithms are required for mobile environment. In this paper, the behavior pattern was classified using naive bayes classification for minimize the loss caused by the omission or error of information. And pattern matching was used to effectively learn of the users inclination and infer the behavior purpose. The accuracy of the suggested inference model was evaluated by applying to the application recommendation service in the smart phones.