• Spatial Information Research
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• v.9 no.1
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• pp.73-89
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• 2001

In the recent rapidly changing technology environment the computerization of administration business using GIS is driven or will be driven to give improved information services for the people by local government or central government with huge budget. Development of GIS for local governments is investigated with huge budge. Development of GIS for local governments is investigated to prevent local government from investing redundant money and to reuse the existing investment at this time. The purpose of this study is finding the development method of Land Management Information System (LMIS) to give service and share data in various computing environment of local governments. To do this, we have to develop LMIS as open system with interoperability and we explain it with a focus to framework of Open LMIS. According to recent trend of technology we developed Open LMIS for convenient maintenance with nationwide LMIS expansion at hand. This system was developed at the $\ulcorner$Land Management Information System Development$\lrcorner$project which was managed by Ministry of Construction and Transportation (MOCT). GIS application was based on OpenGIS CORBA specification for development of standard interface and RUP(Rational Unified Process) for development method and LML(Unified Modeling Language) for system design. Developed systems were land administration system for local government, spatial planning support system for regional government, and land policy support system for MOCT.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.417-423
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• 2017

Recently, many embedded devices that have the computing capability required for deep learning have become available; hence, many new applications using these devices are emerging. However, these embedded devices have an architecture different from that of PCs and high-performance servers. In this paper, we propose a method that improves the performance of deep-learning framework by considering the architecture of an embedded device that shares memory between the CPU and the GPU. The proposed method is implemented in Caffe, an open-source deep-learning framework, and is evaluated on an NVIDIA Jetson TK1 embedded device. In the experiment, we investigate the image recognition performance of several state-of-the-art deep-learning networks, including AlexNet, VGGNet, and GoogLeNet. Our results show that the proposed method can achieve significant performance gain. For instance, in AlexNet, we could reduce image recognition latency by about 33% and energy consumption by about 50%.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.247-254
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• 2013

Storage Class Memory(SCM), such as PRAM, FRAM and MRAM, are expected to be comparable to DRAM in terms of access speed and to Flash memory in terms of capacity in a near future. In this paper, assuming that not only the secondary storage (HDD or Flash memory) but also the primary memory (DRAM) will be replaced by SCM in the future computer systems, we propose an efficient file access framework for the SCM based computer systems. The proposed framework do not assign exclusive area in the SCM to the file system and uses various memory-related techniques, such as unified data access path, zero-copy data read using file mapping, copy-on-write, and multiple page pre-faulting for file management. Based on the preliminary experimental results, we could conclude that the proposed framework can be an efficient baseline for designing a new operating system for the SCM based computer systems.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.81-88
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• 2016

Machine-to-Machine (M2M) communication provides each component (machine) with access to Internet, evolving into the IoT technology. IoT is a trend where numbers of devices provide the communication service, using the Internet protocol. As spreading the concept of IoT(Internet of Things), various objects become home information sources. According to the wide spread of various devices, it is difficult to access data on the devices with unified manners. Under this environment, security is a critical element to create various types of application and service. In this paper propose the inter-device authentication and Centralized Remote Security Provisioning framework in Open M2M environment. The results of previous studies in this task is carried out by protecting it with the latest information on M2M / IoT and designed to provide the ultimate goal of future M2M / IoT optimized platform that can be integrated M2M / IoT service security and security model presents the information.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.83-89
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• 2015

Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.222-236
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• 1997

Conventional solid or surface modeling systems cannot represent both the complete solid model and the abstract model in a unified framework. Recently, non-manifold modeling systems are proposed to solve this problem. This paper describes FlexDesigner, an open kernel system for modeling non-manifold models. It summarizes the data structure for non-manifold models, system design methodology, system modularization, and the typical characteristics of each module in the system. A data structure based on partial-topological elements is adopted to represent the relationship among topological elements. It is efficient in the usage of memory and has topological completeness compared with other published data structures. It can handle many non-manifold situations such as isolate vertices, dangling edges, dangling faces, a mixed dimensional model, and a cellular model. FlexDesigner is modularized hierarchically and designed by the object-oriented methodology for reusability. FlexDesigner is developed using the C++ and OpenGL on both SGI workstation and IBM PC.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.295-298
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• 1996

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

• International Commerce and Information Review
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• v.11 no.4
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• pp.183-214
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• 2009

We identify key theoretical approaches, constructs, and primary variables of interest that exist in the foreign market entry mode articles. This provides fertile ground for continued development in our foreign market entry mode research. Using the integrated framework, this paper examines the determinants of foreign market entry mode choice by Korean firms and the impact of the entry mode choice on performance in a unified model. Using a database of KIS-VALUE in Korea from 2003 to 2005, we find that the hypothesized effects of related factors on entry modes are partially supported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2748-2766
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• 2016

Compared with traditional patch-based sparse representation, recent studies have concluded that group-based sparse representation (GSR) can simultaneously enforce the intrinsic local sparsity and nonlocal self-similarity of images within a unified framework. This article investigates an accelerated split Bregman method (SBM) that is based on GSR which exploits image compressive sensing (CS). The computational efficiency of accelerated SBM for the measurement matrix of a partial Fourier matrix can be further improved by the introduction of a fast Fourier transform (FFT) to derive the enhanced algorithm. In addition, we provide convergence analysis for the proposed method. Experimental results demonstrate that accelerated SBM is potentially faster than some existing image CS reconstruction methods.