• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.618-627
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• 2002

In processing images using 2 dimensional Discrete Wavelet Transform(2D-DWT), the method to process the pixels around the image boundary may affect the quality of image and the cost to implement in hardware and software. This paper proposed an effective method to treat the boundary pixels, which is apt to implement in hardware and software without losing the quality of the image costly. This method processes the 2-D image as 1-D array so that 2-D DWT is performed by considering the image with the serial-sequential data structure (Serial-Sequential Processing). To show the performance and easiness in implementation of the proposed method, an image compression codec which compresses image and reconstructs it has been implemented and experimented. It included log-scale fried quantizer, but the entropy coder was not implemented. From the experimental results, the proposed method showed the SNR of almost the same SNR(Signal to Noise Ratio) to the Periodic Expansion(PE) method when the compression ratio(excluding entropy coding) of 2:1, 15.3% higher than Symmetric Expansion(SE) method, and 9.3% higher than 0-pixel Padding Expansion(ZPE) method. Also PE method needed 12.99% more memory space than the proposed method. By considering only the compression process, SE and ZPE methods needed additional operations than the proposed one. In hardware implementation, the proposed method in this paper had 5.92% of overall circuit as the control circuit, while SE, PE, and ZPE method has 22%, 21,2%, and 11.9% as the control circuit, respectively. Consequently, the proposed method can be thought more effective in implementing software and hardware without losing any image quality in the usual image processing applications.

• Geophysics and Geophysical Exploration
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• v.7 no.3
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• pp.207-212
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• 2004

This article reviews recent developments in three-dimensional (3-D) magntotelluric (MT) imaging. The inversion of MT data is fundamentally ill-posed, and therefore the resultant solution is non-unique. A regularizing scheme must be involved to reduce the non-uniqueness while retaining certain a priori information in the solution. The standard approach to nonlinear inversion in geophysis has been the Gauss-Newton method, which solves a sequence of linearized inverse problems. When running to convergence, the algorithm minimizes an objective function over the space of models and in the sense produces an optimal solution of the inverse problem. The general usefulness of iterative, linearized inversion algorithms, however is greatly limited in 3-D MT applications by the requirement of computing the Jacobian(partial derivative, sensitivity) matrix of the forward problem. The difficulty may be relaxed using conjugate gradients(CG) methods. A linear CG technique is used to solve each step of Gauss-Newton iterations incompletely, while the method of nonlinear CG is applied directly to the minimization of the objective function. These CG techniques replace computation of jacobian matrix and solution of a large linear system with computations equivalent to only three forward problems per inversion iteration. Consequently, the algorithms are efficient in computational speed and memory requirement, making 3-D inversion feasible.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.322-331
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• 2013

The purpose of the present study was to develop a convergent education contents for dementia prevention, operating on the web network applying modern information technology(IT). At the preparation stage, local and worldwide literatures related to dementia were analyzed followed by surveying industry demands, based on which the program was designed and developed. In the following enhancement stage, the program was modified as much as possible by advices obtained from experts in various fields. Development results of the present program are summarized as follows. Firstly, 645 intellect development model to prevent dementia was established through peer review and verification of convergent education theories by expert groups. This model was named as "Garisani" meaning "cognition capable of judging objects" in the Korean language. Secondly, 'Find a way' and 'Connect a line' modules were developed in the numeric field as well as 'Identify a letter(I, II)' modules, in the language field for web-based left brain training program. Thirdly, 'Find my car' and 'Vision training' modules in the attention field and 'Object inference' and 'Compare pictures' modules in the cognition field were developed for web-based right brain training program. Fourth, 'Pentomino' and 'BQmaze'(Brain Quotient and maze) modules in the space perception field and 'Visual training' in the memory field were developed for web-based left and right brains training. Fifth, all results were integrated leading to a 52 week Garisani convergent education program for dementia prevention.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.36-49
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• 2005

Recently, many researchers have given high attention to the semantic web services based on the semantic web technology While existing web services use the XML-based web service description language, WSDL, semantic web services are utilizing web service description languages such as DAML-S in ontology languages. The researchers of semantic web services are generally focused on web service discovery, web service invocation, web service selection and composition, and web service execution monitoring. Especially, the semantic web service discovery as the basis to accomplish the ultimate semantic web service environment has some different properties from previous information discovery areas. Hence, it is necessary to develop the storage system and discovery mechanism appropriate to the semantic well description languages. Even though some related systems have been developed, they are not appropriate for the embedded system environment, such as intelligent robotics, in which there are some limitations on memory disk space, and computing power In this regard, we in the embedded system environment have developed the document management system which efficiently manages the web service documents described by DAML-S for the purpose of the semantic web service discovery, In addition, we address the distinguishing characteristics of the system developed in this paper, compared with the related researches.

• Journal of KIISE
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• v.43 no.10
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• pp.1115-1123
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• 2016

Assumption-based truth maintenance system (ATMS) is a tool that maintains the reasoning process of inference engine. It also supports non-monotonic reasoning based on dependency-directed backtracking. Bookkeeping all the reasoning processes allows it to quickly check and retract beliefs and efficiently provide solutions for problems with large search space. However, the amount of data has been exponentially grown recently, making it impossible to use a single machine for solving large-scale problems. The maintaining process for solving such problems can lead to high computation cost due to large memory overhead. To overcome this drawback, this paper presents an approach towards incrementally maintaining the reasoning process of inference engine on cluster using Spark. It maintains data dependencies such as assumption, label, environment and justification on a cluster of machines in parallel and efficiently updates changes in a large amount of inferred datasets. We deployed the proposed ATMS on a cluster with 5 machines, conducted OWL/RDFS reasoning over University benchmark data (LUBM) and evaluated our system in terms of its performance and functionalities such as assertion, explanation and retraction. In our experiments, the proposed system performed the operations in a reasonably short period of time for over 80GB inferred LUBM2000 dataset.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.18-27
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• 2010

In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.11
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• pp.797-809
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• 2006

To support the QoS streams for large scale clients, the internal resources of VOD servers should be utilized based on the characteristics of the streaming media service. Among the various resources in the server, the main memory is used for the buffer space to the media data loaded from the disks and the buffer hit ratio has a great impact upon the server performance. However, if the buffer data with high hit ratio are replaced for the new media data as a result of the number of clients and the required movie titles are increased, the negative impact on the scalability of server performance is occurred. To address this problem, the buffer replacement policy considers the intrinsic characteristics of the streaming media such as the sequential access to large volume data and the highly disproportionate preference to specific movies. In this paper, the preference-based segment buffer replacement policy is proposed in the cluster-based VOD server to exploit the characteristics of the streaming media. Since the proposed method reflects both the temporal locality by the clients' preference and the spatial locality by the sequential access to media data, the buffer hit ratio would be improved as compared to the existing buffer replacement policy. The enhanced buffer hit ratio causes the fact that the performance scalability of the cluster-based VOD server is linearly improved as the number of cluster nodes is increased.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.298-308
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• 2020

This study was designed to verify reliability and feasibility by analyzing elderly drivers' ability test tools for older drivers aged 65 or older, which were improved in 2018 and are currently being conducted by the Korea Highway Traffic Authority. Only those aged 65 or older who voluntarily applied to the elderly driving ability evaluation system implemented by the Seoul branch of the Korea Highway Traffic Authority. The research was conducted for about 50 days until Aug. 31, 2018, starting with the registration and inspection of the first study subjects. The analysis performed a correlation analysis with existing tools and cognitive testing tools (MMSE_K) to determine their feasibility and reliability as an improved tool in 2018. As a result, the first, the speed distance, time-space memory, and dispersionism of each sub-component of the old version showed statistically significant static correlation with the sub-factor of the current version. Persistence, on the other hand, was not statistically significant to the current version. The limitations of this study were as follows. Most of the people in the study were highly educated and residents in the metropolitan area. Therefore, it is likely that the results of MSE_K, which checks cognitive and judgment skills, have been upgraded. Also, cognitive tools that are measured by computers are likely to have real measurement errors for generations who are not familiar with computers. Therefore, it is expected that improvement and development of tools for improving the limit points at the site and assessing actual operation capability will be required.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.2
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• pp.245-256
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• 2000

A moment-curvature relationship to simulate the behavior of reinforced concrete beam under cyclic loading is introduced. Unlike previous moment-curvature models and the layered section approach, the proposed model takes into consideration the bond-slip effect by using monotonic moment-curvature relationship constructed on the basis of the bond-slip relation and corresponding equilibrium equation at each nodal point. In addition, the use of curved unloading and reloading branches inferred from the stress-strain relation of steel gives more exact numerical result. The advantages of the proposed model, comparing to layered section approach, may be on the reduction in calculation time and memory space in case of its application to large structures. The modification of the moment-curvature relation to reflect the fixed-end rotation and pinching effect is also introduced. Finally, correlation studies between analytical results and experimental studies are conducted to establish the validity of the proposed model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.85-94
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• 2005

Display characterization, deriving the relationship between digital input values and the corresponding CIEXYZ tri-stimulus values, is important to reproduce the accurate color in color management system. The relationship can be estimated from the nine channel TRCs(tone response curves) and the result of this characterization method is better than that of using three channel TRCs. However, the inverse display characterization using nine channel TRCs cannot be directly inverted because the CIEXYZ values corresponding to each of RGB values are inseparable. Accordingly, inverse display characterization is usually implemented by the 3D-LUT (look-up table) method. Although the result of 3B-LUT is accurate, creating the 3D-LUT requires a lot of memory space and considerable amount of measurements. Therefore the inverse characterization method is proposed based on the modeling of channel-dependent values and nine channel inverse process based on the GOG(gain, offset gamma) model. The proposed method enhances the accuracy of display characterization and reduces the complexity and the number of measurements data required for accuracy in 3-D LUT.