• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.50-60
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• 2018

In this paper, we developed a broadband multi-layered radome applicable for high-power applications. In this regard, we presented the wave propagation characteristics of the broadband multi-layered radome with the ABCD matrix and obtained the optimal thickness and the material constant for each layer by an optimization algorithm called "particle swarm optimization," implemented by a commercial numerical modeling tool. Further, we redesigned it in view of mechanical properties to reflect environmental conditions such as wind, snow, and ice. The power transmission property was reanalyzed based on the recalculated data of each layer's thickness to consider the limitations of the fabrication of a large structure. Under the condition of a peak electric field strength that is 10 dB above the critical electric field strength in air breakdown, we analyzed the air breakdown by radio frequency(RF) in the designed radome using the commercial full-wave electromagnetic tool. The radome was manufactured and tested by continuous wave(CW) RF small signal and large signal in an anechoic chamber. The test results showed good agreement with those attained by simulation.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.315-322
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• 2008

Searching a location of the copied video in video database, signatures should be robust to video reediting, channel noise, time variation of frame rate. Several kinds of signatures has been proposed. Ordinal signature, one of them, is difficult to describe the spatial characteristics of frame due to the site of fixed window, $N{\times}N$, which is compute the average gray value. In this paper, I studied an algorithm of sequence matching in video copy detection for the copyright protection, employing the R-tree index method for retrieval and suggesting a robust ordinal signatures for the original video clips and the same signatures of the pirated video. Robust ordinal has a 2-dimensional vector structures that has a strong to the noise and the variation of the frame rate. Also, it express as MBR form in search space of R-tree. Moreover, I focus on building a video copy detection method into which content publishers register their valuable digital content. The video copy detection algorithms compares the web content to the registered content and notifies the content owners of illegal copies. Experimental results show the proposed method is improve the video matching rate and it has a characteristics of signature suitable to the large video databases.

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.33-41
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• 2011

In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.249-262
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• 2005

Optimization problems are formulated to calculate optimal impulses for deflecting Earth-Crossing Objects using a Nonlinear Programming. This formulation allows us to analyze the velocity changes in normal direction to the celestial body's orbital plane, which is neglected in many previous studies. The constrained optimization in the three-dimensional space is based on a patched conic method including the Earth's gravitational effects, and yields impulsive ${\Delta}V$ to deflect the target's orbit. The optimal solution is dependent on relative positions and velocities between the Earth and the Earth-crossing objects, and can be represented by optimal magnitude and angle of ${\Delta}V $ as a functions of a impulse time. The perpendicular component of ${\Delta}V $ to the orbit plane can sometimes play un-negligible role as the impulse time approaches the impact time. The optimal ${\Delta}V $ is increased when the original orbit of Earth-crossing object is more similar to the Earth's orbit, and is also exponentially increased as the impulse time reaches to the impact time. The analyses performed in present paper can be used to the deflection missions in the future.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.836-850
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• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.393-402
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• 2015

Human resources are one of the most essential elements of an organization. In particular, the more closed a group is, the higher the value each member has. Previous studies have focused on personal attributes of individual, such as medical history, and have depended upon self-diagnosis to manage structures. However, this method has weak points, such as the timeconsuming process required, the potential for concealment, and non-disclosure of participants' mental states, as this method depends on self-diagnosis through extensive questionnaires or interviews, which is solved in an interactive way. It also suffers from another problem in that relations among people are difficult to express. In this paper, we propose a multi-faced diagnosis model based on social network analysis which overcomes former weaknesses. Our approach has the following steps : First, we reveal the states of those in a social network through 9 questions. Next, we diagnose the social network to find out specific individuals such as victims or leaders using the proposed algorithm. Experimental results demonstrated our model achieved 0.62 precision rate and identified specific people who are not revealed by the existing methods.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.226-238
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• 2007

In this paper, we present a novel fully distributed topology control protocol that can construct the multiple-ring topology of Minimal Connected Dominating Set (MCDS) as the transport backbone for mobile ad hoc networks. It makes a topology from the minimal nodes that are chosen from all the nodes, and the constructed topology is comprised of the minimal physical links while preserving connectivity. This topology reduces the interference. The all nodes work as the nodes of the distributed parallel Boltzmann machine, of which the objective function is consisted of two Boltzmann factors: the link degree and the connection domination degree. To define these Boltzmann factors, we extend the Connected Dominating Set into a fuzzy set, and also define the fuzzy set of nodes by which the multiple-ring topology can be constructed. To construct the transport backbone of the mobile ad hoc network, the proposed protocol chooses the nodes that are the strong members of these two fuzzy sets as the clusterheads. We also ran simulations to provide the quantitative comparison against the related works in terms of the packet loss rate and the energy consumption rate. As a result, we show that the network that is constructed by the proposed protocol has far better than the other ones with respect to the packet loss rate and the energy consumption rate.