• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.819-833
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• 2013

Computing global features based on local features using a bio-inspired framework has shown promising performance. However, for some tough applications with large intra-class variances, a single local feature is inadequate to represent all the attributes of the images. To integrate the complementary abilities of multiple local features, in this paper we have extended the efficacy of the bio-inspired framework, HMAX, to adapt heterogeneous features for global feature extraction. Given multiple global features, we propose an approach, designated as parameterized metric learning, for high dimensional feature fusion. The fusion parameters are solved by maximizing the canonical correlation with respect to the parameters. Experimental results show that our method achieves significant improvements over the benchmark bio-inspired framework, HMAX, and other related methods on the Caltech dataset, under varying numbers of training samples and feature elements.

• The Journal of Korea Robotics Society
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• v.8 no.3
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• pp.206-216
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• 2013

We investigate the role of contact location information on the perception of local features during contour following in a virtual environment. An absolute identification experiment is conducted under force-alone and force-plus-contact-location conditions to investigate the effect of the contact location information. The results show that the participants identify the local features significantly better in terms of higher information transfer for the force-plus-contact-location condition, while no significant difference was found for measures of the efficacy of contour following between the two conditions. Further data analyses indicate that the improved identification of local features with contact location information is due to the improved identification of small surface features.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.1
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• pp.39-78
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• 2020

In this paper, we propose a decoupled local discontinuous Galerkin method for solving the Klein-Gordon-Schrödinger (KGS) equations. The KGS equations is a model of the Yukawa interaction of complex scalar nucleons and real scalar mesons. The advantage of our scheme is that the computation of the nucleon and meson field is fully decoupled, so that it is especially suitable for parallel computing. We present the conservation property of our fully discrete scheme, including the energy and Hamiltonian conservation, and establish the optimal error estimate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.829-832
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• 2003

This paper presents a technique that allows objects written with local semantics to be made remote. It works by creating interfaces that have roughly the same method signatures as the local interfaces but are remote. These generated interfaces form a layer between the application server interfaces and the RMI runtime. This technique results in the coding of tediously repeated try/catch blocks for the RMI remote interface.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.7-13
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• 2017

In this paper, we propose a novel dynamic subchannel grouping (DSG) algorithm to maximize the system capacity considering intended proper outage probability for the downlink of enterprise small-cell networks (ESNs). In the proposed DSG scheme, a local gateway (LGW) which is installed in a building dynamically divides the frequency bandwidth into different numbers of subchannel groups (SGs) based on the numbers of small-cell access points (SAPs) and small-cell user equipments (SUEs) per floor. Then, the LGW assigns the SGs to SAPs and the SAPs allocate them to their serving SUEs. Through simulation results, we show that the proposed DSG scheme is appropriate for the ESNs compared to the conventional small-cell networks in which all SAPs use the number of fixed SGs in terms of the system capacity and outage probability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.294-296
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• 2017

Cloud computing is a computing technique that uploads all the data from a cloud node to a cloud server and provides it to users as a service. This is difficult to provide services in real time depending on the network conditions. This is because it is necessary to download information to the remote site through the network, not the local area, and to download additional services to provide services in the cloud. So fog computing has been proposed as an alternative. In this paper, we propose an efficient data exchange technique between cloud, fog and user. The proposed fog provides services to users and collects and processes data. The cloud is responsible for the flow of data exchange and control between the fog. We propose a standard method for data exchange. The application for this is to process and service the information generated by the BAN (Body Area Network) in the fog, and the cloud serves as a mediator. This can resolve data heterogeneity between devices or services and provide efficient data movement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1551-1558
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• 2022

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.81-87
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• 2016

With the rapid growth of the up-to-date smartphone and wireless network technologies, huge and various types of smart applications using these technologies are actively developed recently. Especially, multiplex types of smart applications using smartphone are developed and diffused with the rapid development of the ubiquitous sensor network technology using various sensors and the mobile computing technology that enables us to get network services at any time in any places. In this paper, we design a smart application that can accurately diagnose and process the current state of the local environment, objects, and persons remotely based on the context information such as local ecology, circumstances, medical or healthcare records and realtime sound or motion pictures using up-to-date samrtphone technology on the USN based mobile computing environment.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.2
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• pp.45-56
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• 2013

The precise identification of vehicle positions, known as the vehicle localization problem, is an important requirement for building intelligent vehicle ad-hoc networks (VANETs). To solve this problem, two categories of solutions are proposed: stand-alone and data fusion approaches. Compared to stand-alone approaches, which use single information including the global positioning system (GPS) and sensor-based navigation systems with differential corrections, data fusion approaches analyze the position information of several vehicles from GPS and sensor-based navigation systems, etc. Therefore, data fusion approaches show high accuracy. With the position information on a set of vehicles in the preprocessing stage, data fusion approaches is used to estimate the precise vehicular location in the local map building stage. This paper proposes an efficient local map building scheme, which increases the accuracy of the estimated vehicle positions via V2V communications. Even under the low ratio of vehicles with communication modules on the road, the proposed local map building scheme showed high accuracy when estimating the vehicle positions. From the experimental results based on the parameters of the practical vehicular environments, the accuracy of the proposed localization system approached the single lane-level.