• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.2
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• pp.120-127
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• 2015

Purpose: The aim was to investigate the effect of implant thread designs on the stress dissipation of the implant. Materials and methods: The threads evaluated in this study included the V-shaped, buttress, reverse buttress, and square-shaped threads, which were of the same size (depth). Building four different implant/bone complexes each consisting of an implant with one of the 4 different threads on its cylindrical body ($4.1mm{\times}10mm$), a force of 100 N was applied onto the top of implant abutment at $30^{\circ}$ with the implant axis. In order to simulate different osseointegration stages at the implant/bone interfaces, a nonlinear contact condition was used to simulate immature osseointegration and a bonding condition for mature osseointegration states. Results: Stress distribution pattern around the implant differed depending on the osseointegration states. Stress levels as well as the differences in the stress between the analysis models (with different threads) were higher in the case of the immature osseointegration state. Both the stress levels and the differences between analysis models became lower at the completely osseointegrated state. Stress dissipation characteristics of the V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration. These results indicated that implant thread design may have biomechanical impact on the implant bed bone until the osseointegration process has been finished. Conclusion: The stress dissipation characteristics of V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.50-58
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• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.217-225
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• 2011

Currently our country has very serious problems of traffic congestion and urban environment due to increasing automobile ownership. Recently, our concern about environmentally sustainable transportation and green transportation is increasing, so the government is pushing ahead the policy of bicycle using activation. So it is needed to develop a model to analyze the service level of bicycle roads more realistically. In this study, a neuro-fuzzy inference model to analyze the service level of bicycle roads was built selecting the width of bicycle roads, the number of conflicts during cycling and pedestrian volume, which have fuzzy characteristics, as input variables. The predictability of the model was evaluated comparing the surveyed and the estimated. The values of the statistics, $R^2$, MAE and MSE were 0.987, 0.142, 0.032. Therefore, It may be judged that the explainability of the model is very high. The service levels of bicyle roads estimated by the model are 1~3 steps lower than KHCM assessments. The reason may be explained that the model estimates the service level considering the width of bicycle roads and the number of conflicts simultaneously besides pedestrian volume.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.617-626
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• 2009

A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a ${\delta}$-sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the ${\delta}$-sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.

• Economic and Environmental Geology
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• v.36 no.4
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• pp.295-304
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• 2003

The Dukpyung and the Chubu areas were selected to investigate the migration and enrichment of arsenic and other toxic elements in soils and crop plants in areas covered with black shales. Rock and soil samples digested in 4-acid solution (HCI+HNO$_3$+HF+HC1O$_4$) were analyzed fer arsenic and other heavy metals by ICP-AES and ICP-MS, and plant samples by INAA. Mean concentration of As in Okchon black shale is higher than those of both world average values of shale and black shale. Especially high concentration of 23.2 mg/kg As is found in black shale from the Dukpyung area. Mean concentration of As is highly elevated in agricultural soils from the Duk-pyung (28.2 mg/kg) and the Chubu areas (32.6 mg/kg). Arsenic is highly elevated in rice stalks and leaves from the Dukpyung (1.14 mg/kg) and the Chubu areas (1.35 mg/kg). The biological absorption coefficient (BAC) of As in plant species decreases in the order of rice leaves>com leaves>red pepper>soybean leaves=sesame leaves>corn stalks>corn grains.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.205-227
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• 2002

Our study is focused on a multiple-agent system to provide efficient collaborative work by automating the conference calling process with the help of intelligent agents. Automating the meeting scheduling requires a careful consideration of the individual official schedule as well as the privacy and personal preferences. Therefore, the automation of conference calling needs the distributed processing task where a separate calendar management process is associated for increasing the reliability and inherent parallelism. This paper describes in detail the design and implementation issues of a multiple-agent system for conference calling that allows the convener and participants to minimize their efforts in creating a meeting. Our system is based on the client-sewer model. In the sewer side, a scheduling agent, a negotiating agent, a personal information managing agent, a group information managing agent, a session managing agent, and a coordinating agent are operating. In the client side, an interface agent, a media agent, and a collaborating agent are operating. Agents use a standardized knowledge manipulation language to communicate amongst themselves. Communicating through a standardized knowledge manipulation language allows the system to overcome heterogeneity which is one of the most important problems in communication among agents for distributed collaborative computing. The agents of our system propose the dates on which as many participants as possible are available to attend the conference using the forward chaining algorithm and the back propagation network algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.210-217
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• 2013

The development of collaboration among information systems in accordance with changes in enterprises' business environment brings about the problems of duplication of the existing business services and increase in costs of maintenance. Accordingly, Web service has been suggested as the standard of distributed computing to prevent the duplication of services within the same business domain and to attain the services that are already being utilized. But since the data needed for Web services are not standardized, it is difficult for the users to find services that meet diverse business purposes. In this paper, we construct an ontology-based collaboration system for service interoperability. The ontology can support fusion service by finding services which are existed interdependently under the distributed environment for collaboration processing. The role of the collaborative system includes development, registration and call of services based on ontology. A local systems request collaboration support through the service profile. Collaborative system supports the development of service using the service profiles, represents the semantic association between real data through system ontology, and infers relationship between instances contained in the services. Based on this, we applied the travel booking services for collaboration system. As a result, service can be managed effectively preventing collision in collaborative system, and we verify that the mapping between system is reduced.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.51-58
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• 2008

Wireless sensor networks are used by various application areas to implement smart data processing and ubiquitous system. In the recent research of parking management system based on wireless sensor networks, adaptive sensing and efficient data processing are not considered. The effectiveness of implementing these distributed computing devices affects the performance of the applications in parking management. This paper proposes an adaptive sensing using fuzzy wireless sensor for the ubiquitous networks of parking management system. The fuzzy inference system is encoded in the sensor for efficient car presence detection. Moreover, a rule base adaptive module is proposed which wirelessly transmit the new values to each sensor for adapting the environment of car park area. The result of experiments shows that the fuzzy wireless sensor provides more throughputs and less time delays compared to a normal method of data gathering by wireless sensors.

• Journal of the Korean School Mathematics Society
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• v.23 no.3
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• pp.239-257
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• 2020

This study analyzes the degree of freedom with three aspects: as academic knowledge, in the curriculum focused on textbooks, and students' understanding of the degree of freedom. The results provide five critical points. First, we need discussions on whether to include the degree of freedom in the curriculum. Second, we need to reconsider the current way textbooks are described. Third, there should be a didactical analysis to advance students' understanding of the concept of the degree of freedom. Fourth, there are limitations in learning the concept of the degree of freedom in the current textbook learning environment. Fifth, a didactical check of sampling distribution such as sample mean, sample variance, and sample standard deviation is required. The implications were drawn that the emphasis on statistical reasoning education in the curriculum and careful consideration of introducing the t-distribution curriculum was required.