• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.1-14
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• 2024

The most optimal route-search algorithm thus far has introduced a method of applying node labels and link labels. Node labels consider two nodes simultaneously in the optimal route-search process, while link labels consider two links simultaneously. This study proposes a turn-label-based optimal route-search technique that considers two turns simultaneously in the process. Turn-label-based optimal route search guarantees the optimal solution of dynamic programming based on Bellman's principle as it considers a two-turn search process. Turn-label-based optimal route search can accommodate the advantages of applying link labels because the concept of approaching the limit of link labels is applied equally. Therefore, it is possible to reflect rational cyclic traffic where nodes allow multiple visits without expanding the network, while links do not allow visits. In particular, it reflects the additional cost structure that appears in two consecutive turns, making it possible to express the structure of the travel-cost function more flexibly. A case study was conducted on the metropolitan urban railway network consisting of transportation card terminal readers, aiming to examine the scalability of the research by introducing parameters that reflect psychological resistance in travel with continuous pedestrian transfers into turn label optimal path search. Simulation results showed that it is possible to avoid conservative transfers even if the travel time and distance increase as the psychological resistance value for continuous turns increases, confirming the need to reflect the cost structure of turn labels. Nevertheless, further research is needed to secure diversity in the travel-cost functions of road and public-transportation networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.795-806
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• 1996

A structure which transmits and receives 3 subscribers packet data through an optical splitter node in an optical subscriber network of PON wave suggested and realized. All the functions which are necessary to use PON structure such as 155.52Mb/s multiplexer/demultiplexer of down-stream signal, 25.92Mb/s multiplexer/demultiplexer of up-stream signal, frame synchronizer, and phase aligner for aligning phase of the clock and received data have been integrated within 2 ICs using CMOS technonology. TDMAtechnology was suggested for up-stream transmission. In the optical up-stream transmission of the urst signals transmissionquality degradataion by APC and AGC of optical tranceiver was observed. By compensating the degradation, more than 17dB of link budget which is enough to satisfy 11.2dBthat is required in SWAN of PON architecture has been obtained with optical transceiver whose power and sensitivity are -17dBm and -34dBm respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.4
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• pp.398-414
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• 1992

For designing the radar integrated data network, we construct the network structure with a spatial hierarchy decomposition scheme. The RIDN can be decomposed into several subnet classes, those of which are composed of the several group classes of radar sits, In a group class, the communication nodes of a radar site are modeled by the software modules formulated with the statistical attributes of discrete events. And we get the analysis over the network through the separately constructed infra group level models which were coded with the C language. After constructing the local area network with these infra models through the proper data links. We got the analysis of the communication performance of inner models and the global network.

• The Journal of Information Systems
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• v.9 no.1
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• pp.27-44
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• 2000

The structure of neural networks is represented by a weighted directed graph with nodes representing units and links representing connections. Each link is assigned a numerical value representing the weight of the connection. In learning process, the values of weights are adjusted by errors. Following experiment results, the interval of adjusting weights, that is, epoch size influenced neural networks＇ performance. As epoch size is larger than a certain size, neural networks＇performance decreased drastically. And the number of hidden layer＇s node also influenced neural networks＇performance. The networks＇performance decreased as hidden layers have more nodes and then increased at some number of hidden layer＇s node. So, in implementing of neural networks the epoch size and the number of hidden layer＇s node should be decided by systematic methods, not empirical or heuristic methods.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1320-1330
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• 2017

Wireless sensor networks for forest monitoring are typically deployed in fields in which manual intervention cannot be easily accessed. An interesting approach to extending the lifetime of sensor nodes is the use of energy harvested from the environment. Design constraints are application-dependent and based on the monitored environment in which the energy harvesting takes place. To reduce energy consumption, we designed a power management scheme that combines dynamic duty cycle scheduling at the network layer to plan node duty time. The dynamic duty cycle scheduling is realized based on a tier structure in which the network is concentrically organized around the sink node. In addition, the multi-paths preserved in the tier structure can be used to deliver residual packets when a path failure occurs. Experimental results show that the proposed method has a better performance.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.16-18
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• 2001

Despite extensive research on R-trees, most of the proposed schemes have not been integrated into existing DBMS due to the lack of protocol to provide consistency in concurrent environment. R-link tree is an acceptable data structure to deal with this issue., but still not enough. In this paper, we focus on a simplified predicate locking mechanism based on R-link tree for concurrency control and phantom protection. An in-memory operation control list (OCList) used to suspend some conflicting operations is designed here. The main features of this approach are (1) it can be implemented easily and do not need any extra information. (2) Only-one-lock is held when descending R-tree even when node split happens, while lock-coupling scheme is performed when ascending. No deadlocks are possible. (3) Searches and insertions are not unnecessarily restricted. (4) Insert and Delete phantom in R-link tree are avoid through beforehand predication.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.5
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• pp.199-204
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• 2006

To develop a safety-critical network in nuclear power plants that puts more stringent requirements than the competitive commercial ones do, we establish four design criteria - deterministic communication, explicit separation/isolation structure, reliability, verification & validation. According to those design criteria, the fundamental design elements are chosen as follows - a star topology, point-to-point physical link, connection-oriented link control and fixed allocation access control. After analyzing the design elements, we also build a communication architecture with TDM (Time Division Multiplexing) bus switching scheme. Finally, We develop a DDCNet (Deterministic Data Communication Network) based on the established architecture. The DDCNet is composed of 64 nodes and guarantees the transmission bandwidth of 10Mbps and the delay of 10 msec for each node. It turns out that the DDCNet satisfies the aforementioned design criteria and can be adequately utilized for our purpose.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1828-1834
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• 2004

With the rapid development of wireless communications and mobile technologies, requirements of various services based on moving objects like location-based services and mobile applications services have been increased. In this paper, we propose an index structure which can improve the performance on trajectory-based query especially, one of the various query types for moving objects in mobile applications. It maintains link table(L-Table) to obtain good efficiency on retrieval and insertion performance of the existing TB(Trajectory Bundle)-tree proposed for trajectory-based query of moving objects. The L-Table contains page number in disk and memory pointers pointing the leaf node with the first and last line segment of moving objects in order to directly access preceding node. In addition, we design to reside a part of whole index in main memory by preserving a fixed size of buffer in case of being restricted by available main memory. Finally, experimental results with various data sets show that the proposed technique is superior to the existing index structures with respect to insertion and trajectory-based query.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.262-265
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• 2008

We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.39-57
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• 2018

The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.