• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1098-1104
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• 2010

Recently, a variety of research of multi-hop routing protocol have been done to balance the sensor node energy consumption of WSN(wireless sensor network) and to improve the node efficiency for extending the life of the entire network. Especially in multi-hop protocol, a variety of models have been concerned to improve energy efficiency and apply in the reality. In multi-hop protocol, we assumption that energy consumption can be adjusted based on the distance between the sensor nodes. However, according to the physical property of the actual WSN, it's hard to establish this assumption. In this dissertation, we propose low-power sub-cluster protocol to improve the energy efficiency based on the spread of distance. Compared with the previous protocols, this proposed protocol can be effectively used in the wireless sensing networks.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.647-656
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• 2008

In this paper, we present interference power distribution results when radio frequency identification(RFID) and ubiquitous sensor network(USN) systems share the $908.5{\sim}914MHz$ frequency bands. Average interference powers are obtained by simulation and statistical analysis, respectively. Simulation results are then verified by statistical analysis. According to the number of interferers and the diameter of the protection area, the cumulative density functions(CDFs) of interference power are simulated under the various conditions. From the simulation results, the probability that both USN and RFID systems meet the required maximal interference power levels is 95 % on condition that there are 1 low revered RFID reader and several USN nodes and that the minimum distance between a RFID reader and an USN node is greater than 1 m. Our results can be used as an basic research for coexistence analysis of RFID and USN systems in the $908.5{\sim}914MHz$ frequency bands.

• Journal of KIISE
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• v.42 no.3
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• pp.408-412
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• 2015

In base station based networks, traffic overload at the base station is inevitable. Peer-to-peer DTN which disperses the traffic overhead to each node can relieve the traffic overload at the base station. To increase the message delivery ratio and reduce the message overhead, we present novel routing using mobility information which can be obtained from each node, unlike the existing flooding based routings. In the proposed routing scheme, the routing decision metric, which is defined based on the node mobility information, is computed by using the expected distance between each node to the destination. The message is copied to other nodes that have lower expected distance to the destination than the value for the node willing to copy the message. We conducted simulations by using both a random mobility model and a real mobility trace to compare the performance of the proposed routing scheme to the existing routing scheme that does not utilize the mobility information. The performance evaluation showed the proposed routing successfully delivers messages with 10% to 30% less copies compared to previously proposed routing schemes.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.131-138
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• 2008

Mobile Ad hoc NETworks (MANETs) refer to autonomous networks in which wireless data communications are established between multiple nodes in a given coverage area without a base station or centralized administration. Because of node mobility and limited battery life, the network topology may changes frequently. Selecting the most reliable path during route discovery process is important to improve performance in ad hoc networks. In this paper, an enhanced routing protocol based on AODV(Ad hoc On-demand Distance Vector routing) by monitoring variation of receiving signal strength is proposed. New metric function that consists of node mobility and hops of path is used for routing decision. For preventing route failure by node movement during data transmission, a new route maintenance named as LRC (Local Route Change) is presented. If the node movement is detected, the routing agent switches path to its neighbor node in LRC. Simulation results show that the performance of the proposed routing scheme is superior to previous AODY protocol.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.343-349
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• 2022

This paper proposes a new topology optimization scheme to determine optimized joints for multi-component models. The joints are modeled as zero-length high-stiffness spring elements. The spring joints are considered as mesh-independent springs based on a joint-element interpolation scheme. This enables the changing of the location of the joints regardless of the connected nodes during optimization. Because the joints are movable, the locations of the optimized joints should be aggregated at several points. In this paper, the novel joint dispersal (JD) constraint to prevent joint clustering is proposed. With the joint dispersal constraint, it is possible to determine the optimized joint location as well as optimized topologies while maintaining the minimum distance between each joint. The mechanical compliance value is considered as the objective function. Several topology optimization examples are solved to demonstrate the effect of the joint dispersal constraint.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.15-22
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• 2023

An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1207-1215
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.