• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2003.09a
• /
• pp.8-12
• /
• 2003

Crustal velocity model is very important to determine the hypocenters of the local earthquakes, because the real crust is more complex and heterogeneous than simple homogeneous layered model. But the exact crust model in and around Kyeongsang basin area is not fixed till now. To solve this problem, Joint Hypocenter Determination(JHD) method is applied to the 151 local earthquakes, that is recorded at KIGAM local network from Mar. 25, 1999 to Dec. 16, 2001. According to the comparison of earthquake locations and depths for the conventional procedure and JHD relocation procedure, each locations is very similar, but depth distributions are different. An initial depth distribution derived from the conventional methods is irregular and does not show the general trends. JHD relocations reduce scatter and define a dipping plane.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.3 no.2
• /
• pp.245-253
• /
• 1999

This paper was studied on utilization method of information in Tong-yeong area of which main industry is fisheries. The three kinds of network models such as Marine Information Network Model, Fisheries Industry Information Network Model, Fisheries Products Marketing Information Model were suggested with a method maximizing the utilization value of information. Marine Information Network Model dealt with information on marine environment and marine biology, Fisheries Industry Information Network with information on fisheries and fisheries culture industry, and Fisheries Products Marketing Information with information on fish and fisheries culture products marketing. Service on the Web base was made possible so that a final user got the most recent information, treating on real-time base data collected from each information network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.05a
• /
• pp.70-77
• /
• 1999

This paper was studied on utilization method of information in Tong-yeong area of which main industry is fisheries. The three kinds of network models such as Marine Information Network Model, Fisheries Industry Information Network Model, Fisheries Products Marketing Information Model were suggested with a method maximizing the utilization value of information. Marine Information Network Model dealt with information on marine environment and marine biology, Fisheries Industry Information Network with information on fisheries and fisheries culture industry, and fisheries Products Marketing Information with information on fish and fisheries culture products marketing. Service on the Web base was made possible so that a final user got the most recent information, treating on real-time base data collected from each information network.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.799-810
• /
• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.5
• /
• pp.209-216
• /
• 2013

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.3
• /
• pp.1030-1050
• /
• 2021

The edges with "bridge characteristic" play the role of connecting the communication between regions in power optical cable network. To solve the problem of mining edges with "bridge characteristic" in provincial power optical cable network, the complex power optical cable network model is constructed. Firstly, to measure the generated potential energy of all nodes in n-level neighborhood local structure for one edge, the n-level neighborhood local structure topological potential is designed. And the minimum connected chain attenuation is designed to measure the attenuation degree caused by substituted edges. On the basis of that, the minimum connected chain attenuation topological potential based measurement is designed. By using the designed measurement, a bridge-edges mining algorithm is proposed to mine edges with "bridge characteristic". The experiments are conducted on the physical topology of the power optical cable network in Jilin Province. Compared with that of other three typical methods, the network efficiency and connectivity of the proposed method are decreased by 3.58% and 28.79% on average respectively. And the proposed method can not only mine optical cable connection with typical "bridge characteristic" but also can mine optical cables without obvious characteristics of city or voltage, but it have "bridge characteristic" in the topology structure.

• Journal of Information Processing Systems
• /
• v.17 no.2
• /
• pp.242-252
• /
• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• Korean Security Journal
• /
• no.42
• /
• pp.7-36
• /
• 2015

This study aims at analyzing difference of social Security network, Community unity and local government trust according to socio-demographical features, exploring the relation of social Security network, Community unity and local government trust according to socio-demographical features, presenting results between each variable as a model and verifying the property of mutual ones. This study sampled general citizens in Gwangju for about 15 days Aug. 15 through Aug. 30, 2014, distributed total 450 copies using cluster random sampling, gathered 438 persons, 412 persons of whom were used for analysis. This study verified the validity and credibility of the questionnaire through an experts' meeting, preliminary test, factor analysis and credibility analysis. The credibility of questionnaire was ${\alpha}=.809{\sim}{\alpha}=.890$. The inout data were analyzed by study purpose using SPSSWIN 18.0, as statistical techniques, factor analysis, credibility analysis, correlation analysis, independent sample t verification, ANOVA, multi-regression analysis, path analysis etc. were used. the findings obtained through the above study methods are as follows. First, building a social Security network has an effect on Community institution. That is, the more activated a, the higher awareness on institution. the more activated street CCTV facilities, anti-crime design, local government Security education, the higher the stability. Second, building a social Security network has an effect on trust of local government. That is, the activated local autonomous anti-crime activity, anti-crime design. local government's Security education, police public oder service, the more increased trust of policy, service management, busines performance. Third, Community unity has an effect on trust of local government. That is, the better Community institution is achieved, the higher trust of policy. Also the stabler Community institution, the higher trust of business performance. Fourth, building a social Security network has a direct or indirect effect on Community unity and local government trust. That is, social Security network has a direct effect on trust of local government, but it has a higher effect through Community unity of parameter. Such results showed that Community unity in Gwangju Region is an important factor, which means it is an important variable mediating building a social Security network and trust of local government. To win trust of local residents, we need to prepare for various cultural events and active communication space and build a social Security network for uniting them.

• Journal of the Korean Geotechnical Society
• /
• v.24 no.11
• /
• pp.17-24
• /
• 2008

It is known that scour at bridge piers is one of the leading causes of bridge failure. However, the mechanism of flow around a pier structure is so complicated that it is difficult to establish a general empirical model to provide accurate estimation for scour. Especially, each of the proposed empirical formula yields good results for a particular data set but can't show reliable predictability for various scouring data set. In this study, an alternative approach, that is, artificial neural networks (ANN), is proposed to estimate the local scour depth with numerous field data base. The local scour depth was modeled as a function of seven variables; pier shape, pier width, pier length, skew angle, stream velocity, water depth, $D_{50}$. 426 field data were used for the training and testing of ANN model. The predicted results showed that the neural network could provide a better alternative to the empirical equations.

• Journal of KIISE:Information Networking
• /
• v.31 no.2
• /
• pp.217-223
• /
• 2004

This paper proposes a new backoff scheme to improve the throughput of stations over wireless local area networks. It is designed to carry out the proposed backoff scheme using information of basic service area, such as number of stations, in terms of the throughput. Basic idea of the proposed backoff scheme is that we change the contention window size for backoff time as collisions increase. We evaluate the performance of the proposed backoff scheme using Markov model analysis and compare it with the IEEE 802.11e backoff scheme. The numerical results indicate that the Proposed backoff scheme may offer better performance than the conventional backoff scheme in terms of the throughput.