• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.907-913
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• 2004

The major interest of general mobile robot is making a route and following a maked route. But, In the case of robot that is in need of movement of partial high speed, the condition of dynamic limitation is exist, and in these conditions, it demands controlling against movements we want. In this paper, in respect of the following a route at the situation that don't have the environmental map, that is, unknown environments, to prevent the slide of moving robot or the overturn that can happen for it moves fast, we organize the dynamic condition of limitation using the fuzzy logic, and we obtain more safe and fast route tracing ability by changing the standard velocity. Especially, by modeling the line tracing mobile robot, we design the tracing controller against a realtime changing target, and using the fuzzy optimized velocity limitation controller, we confirm that our robot shows its stable tracing ability by limiting its velocity intelligently against the continuously changing line.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1905-1912
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• 2009

Clustering results based on the FCM algorithm sometimes produces undesirable clustering result through data distribution in the clustered space because data is classified by comparison with membership degree which is calculated by the Euclidean distance between input vectors and clusters. Symmetrical measurement of clusters and fuzzy theory are applied to the classification to tackle this problem. The enhanced FCM algorithm has a low impact with the variation of changing distance about each cluster, middle of cluster and cluster formation. Improved hybrid network of applying FCM algorithm is proposed to classify patterns effectively. The proposed enhanced FCM algorithm is applied to the learning structure between input and middle layers, and normalized delta learning rule is applied in learning stage between middle and output layers in the hybrid network. The proposed algorithms compared with FCM-based RBF network using Max_Min neural network, FMC-based RBF network and HCM-based RBF network to evaluate learning and recognition performances in the two-dimensional coordinated data.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.271-276
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• 2016

In this paper, we propose robust face and eye detection algorithm under changing environmental condition such as lighting and pose variations. Generally, the eye detection process is performed followed by face detection and variations in pose and lighting affects the detection performance. Therefore, we have explored face detection based on Modified Census Transform algorithm. The eye has dominant features in face area and is sensitive to lighting condition and eye glasses, etc. To address these issues, we propose a robust eye detection method based on Gabor transformation and Features from Accelerated Segment Test algorithms. Proposed algorithm presents 27.4ms in detection speed with 98.4% correct detection rate, and 36.3ms face detection speed with 96.4% correct detection rate for eye detection performance.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.97-110
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• 2016

Cryptanalysis is very important step for auditing and checking strength of any cryptosystem. Some of these cryptosystem ensures confidentiality and security of large information exchange from source to destination using symmetric key cryptography. The cryptanalyst investigates the strengths and identifies weakness key as well as enciphering algorithm. With increase in key size the time and effort required to guess the correct key increases so trend is increase key size from 8, 16, 24, 32, 56, 64, 128 and 256 bits to strengthen the cryptosystem and thus algorithm continues without compromise on the cost of time and computation. Automatic Variable Key (AVK) approach is an alternative to the approach of fixing up key size and adding security level with key variability adds new dimension in the development of secure cryptosystem. Likewise, whenever any new cryptographic method is invented to replace per-existing vulnerable cryptographic method, its deep analysis from all perspectives (Hacker / Cryptanalyst as well as User) is desirable and proper study and evaluation of its performance is must. This work investigates AVK based cryptic techniques, in future to exploit benefits of advances in computational methods like ANN, GA, SI etc. These techniques for cryptanalysis are changing drastically to reduce cryptographic complexity. In this paper a detailed survey and direction of development work has been conducted. The work compares these new methods with state of art approaches and presents future scope and direction from the cryptic mining perspectives.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.5
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• pp.479-487
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• 2009

This paper describes the design of a full-spade twisted rudder section by using the genetic algorithm based on VLM(Vortex Lattice Method) and panel method. The developed propeller- rudder analysis program has been validated by comparing with experimental data. The developed code has been used for the design of a twisted full-spade rudder especially for finding out optimum section. The optimization has been firstly carried out by the genetic algorithm. The more detail variation of a rudder section has been also conducted by changing section profile in more detail to confirm the most optimum section profile. The developed new twisted rudder has been compared with existing twisted rudder by cavitation testing in the cavitation tunnel at MOERI. It is concluded that the developed twisted rudder has a lower cavity in comparison with existing twisted rudder. The verification of efficiency gain is expected to be carried out through self-propulsion tests in the near future.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.807-812
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• 2020

This paper proposes a blind speech source separation algorithm using a microphone to separate only the target speech source signal in an environment in which various speech source signals are mixed. The proposed algorithm is a model of frequency domain representation based on independent component analysis method. Accordingly, for the purpose of verifying the validity of independent component analysis in the frequency domain for two speech sources, the proposed algorithm is executed by changing the type of speech sources to perform speech sources separation to verify the improvement effect. It was clarified from the experimental results by the waveform of this experiment that the two-channel speech source signals can be clearly separated compared to the original waveform. In addition, in this experiments, the proposed algorithm improves the speech source separation performance compared to the existing algorithms, from the experimental results using the target signal to interference energy ratio.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.188-194
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• 2014

The feature extraction mechanism of the CASA(Computational Auditory Scene Analysis) system uses time continuity and frequency channel similarity to compose a correlogram of auditory elements. In segmentation, we compose a binary mask by using cross-correlation function, mask 1(speech) has the same periodicity and synchronization. However, when there is delay between autocorrelation signals with the same periodicity, it is determined as a speech, which is considered to be a drawback. In this paper, we proposed an algorithm to improve discrimination of channel similarity using Weighted Cross-correlation in segmentation. We conducted experiments to evaluate the speech segregation performance of the CASA system in background noise(siren, machine, white, car, crowd) environments by changing SNR 5dB and 0dB. In this paper, we compared the proposed algorithm to the conventional algorithm. The performance of the proposed algorithm has been improved as following: improvement of 2.75dB at SNR 5dB and 4.84dB at SNR 0dB for background noise environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.261-268
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• 2013

In this paper, we propose the algorithm that improves the linearity of the walking assistant robot on lateral slopes. The walking assistant robot goes out of the course due to the rotational moment which is caused by the weight of the robot and the slope. To compensate this, we give the weight to each driving axle after comparing the real rotational angular velocity with the target rotational angular velocity which is entered by an user. The results of applying the algorithm to the real walking assistant robot show that the yaw axis deviation of the robot without the algorithm diverges, but the yaw axis deviation of the robot with the algorithm lies within 20cm, which can be recognized as stable. In addition, the changing rate of the course deviation is stabilized and shows no more course deviation, after moving 300cm.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.45-57
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• 2009

BTL (Build-Transfer-Lease) Project for Education Facilities are contracted as a package which consists of several education facilities. The general maintenance period of BTL project for education facilities is 20 years. Thus, total cost variation largely depends on the accuracy of the maintenance cost forecasting in the early stage in the life cycle of the BTL Project. This research develops a cost forecasting system using complete linkage algorithm and branch & bound algorithm to help in finding optimal bundling combination. This system helps owner's decision-making to estimate the total project cost with various constraints changing. The result of this research suggests more reasonable and effective forecasting model for the maintenance facilities package in the BTL project.