• Steel and Composite Structures
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• v.24 no.4
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• pp.425-439
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• 2017

As a thin-walled structure, local joint flexibility (LJF) in a tubular structure is prominent, and it may produce significant effect on the static performance for the overall structure. This study presents a simplified analytical model to analyze the static behavior for a steel tubular structure with LJF. The presented model simplifies a tubular structure into a frame model consisted of beam elements with considering the LJFs at the connections between any two elements. Theoretical equations of the simplified analytical model are deduced. Through comparison with 3-D finite element results of two typical planar tubular structures consisted of T- and Y-joints respectively, the presented method is proved to be accurate. Furthermore, the effect of LJF on the overall performance of the two tubular structures (including the deflection and the internal forces) is also investigated, and it is found from analyses of internal forces and deformation that a rigid connection assumption in a frame model by using beam elements in finite element analysis can provide unsafe and inaccurate estimation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.33-42
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• 2003

In this paper, we propose an enhancement of the ultrasonic image for non-destructive inspection of aircraft composite materials. The ultrasonic images are corrupted by a speckle noise which has the characteristic of granular pattern noise and is in all types of coherent imaging systems, the signal independent and multiplicative noise. In this paper, we derive a filter, called the AWLF(Adaptive Window Log Filter), from the nature of the speckle. The filter is made of the MEAN Filter in the edge region and Log Filter in the flat or noise region. To make a distinction between edge and flat region, we calculate the inclination around the local window instead of computing the local statistics of pixels such as local mean ${\bar{M}}$ and standard deviation ${\sigma}_s$. According to the obtained region, edge region is performed by the mean filter and flat region by the Log filter. Performance of the proposed filter is evaluated by the Enhanced Factor$(F_e)$ and the Speckle Index(SI).

• School Mathematics
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• v.8 no.3
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• pp.291-300
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• 2006

Proofs in school mathematics are regarded as the procedures to examine a proposition's truth or falsehood. However, they are not based on an axiomatic system in general. This implies the possible existence of vicious circles in proofs in school mathematics. The concept of proof can be more completely acquired when accompanied with concept of circular reasoning and necessity of axiomatic system. Therefore, it is necessary to discuss on the axiomatic system in school mathematics curriculum. The vicious circle can be found in computing an area of a circle by using definite integral in differentiation/integration part of high school textbooks. This paper will first illustrate this in detail and then offer several comments on the axiomatic methods related to the dissolution of that circular reasoning. To further the discussion, Archimedes' derivation for the area of a circle will be considered next. Finally, several arguments on circular reasoning, local organization, and axiomatic system in school curriculum will be presented at the end of the paper.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.128-136
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• 2008

In this paper, we propose a variable step search fast motion estimation algorithm using local statistics of neighboring motion vectors. Using the degree of correlation between neighboring motion vectors, motion search range is adaptively adjusted to reduce unnecessary search points. Based on the adjusted search range, motion vector is obtained by variable search step. Experimental results show that the proposed algorithm has the capability to dramatically reduce the search points and computing cost for motion estimation, comparing to fast full spiral search motion estimation and other fast motion estimation.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.121-128
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• 2004

This paper proposes a quality evaluation system of a handwriting string written by electronic pen. For the purpose of the system, this paper describes how to retrieve reference data from a database, how to evaluate the quality of a handwiting string using global and local features. Also, it explains how to optionally recognize a grade of a handwriting string at using global and how to diagnose stroke order at using local. The quality can be evaluated in the case of different language between reference and input by the system. Therefore, we expect that the system is very useful not only for training on handwriting but also for learning a language.

• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4268-4290
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• 2015

Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.115-126
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• 2008

VNC(Virtual Network Computing) is a desktop sharing system based on the RFB(Remote Framebuffer) protocol which allows you to control a remote computer running a VNC server through a VNC client(or viewer) on a local computer. To exchange information between the two computers, VNC provides the functionality of sharing the clipboard contents. Unfortunately, the current VNC softwares support only the clipboard text contents, not providing methods for sharing the clipboard multimedia contents such as images. In this paper, we extend the RFB protocol to share the clipboard contents composed of text and images. Also, to support the developed protocol. we extend both the UltraVNC server and the JavaViewer VNC client which are free open-source softwares. Through the developed VNC softwares, users can exchange the clipboard contents including texts and images between the remote computer and the local computer.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.