• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1925-1936
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• 2010

In this paper, multi-legged robot was designed and produced using stable walking pattern algorithm. The robot had embedded camera and wireless communication function and it is possible to recognize both hand posture and obstacles. The algorithm decided moving paths, and recognized and avoided obstacles through Hough Transform using Edge Detection of inputed image from image sensor. The robot can be controlled by hand posture using Mahalanobis Distance and average value of skin's color pixel, which is previously learned in order to decide the destination. The developed system has shown obstacle detection rate of 96% and hand posture recognition rate of 94%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1386-1391
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• 2018

The radar in the moving platform is interfered by the mainlobe clutter as well as the altitude clutter that is received from sidelobe. The altitude clutter is relatively short range compared to mainlobe clutter and therefore enters the radar with a strong signal. As these clutters are major reason making the probability of false alarm high, it is required to suppress both altitude clutter and mainlobe clutter. In this paper, It is proposed the clutter suppression method consisted of two pulse canceller to suppress the clutters being two frequency area in moving platform. It is analyzed the correlation of output signals according to the use of pulse canceller and provided the structure of staggered pulse canceller considered the correlation. Finally, it shows that altitude clutter and mainlobe clutter are suppressed by proposed staggered pulse canceller using the simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3434-3439
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• 2015

As a criterion of information theoretic learning, the Euclidean distance (ED) of two error probability distribution functions (minimum ED of error, MEDE) has been adopted in nonlinear (decision feedback, DF) supervised equalizer algorithms and has shown significantly improved performance in severe channel distortion and impulsive noise environments. However, the MEDE-DF algorithm has the problem of heavy computational complexity. In this paper, the recursive ED for MEDE-DF algorithm is derived first, and then the feed-forward and feedback section gradients for weight update are estimated recursively. To prove the effectiveness of the recursive gradient estimation for the MEDE-DF algorithm, the number of multiplications are compared and MSE performance in impulsive noise and underwater communication environments is compared through computer simulation. The ratio of the number of multiplications between the proposed DF and the conventional MEDE-DF algorithm is revealed to be $2(9N+4):2(3N^2+3N)$ for the sample size N with the same MSE learning performance in the impulsive noise and underwater channel environment.

• Land and Housing Review
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• v.2 no.4
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• pp.407-413
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• 2011

This paper reports a novel structural health monitoring (SHM) technique for detecting de-bonding between a concrete beam and CFRP (Carbon Fiber Reinforced Polymer) sheet that is attached to the concrete surface. To achieve this, a multi-scale actuated sensing system with a self-sensing circuit using piezoelectric active sensors is applied to the CFRP laminated concrete beam structure. In this self-sensing based multi-scale actuated sensing, one scale provides a wide frequency-band structural response from the self-sensed impedance measurements and the other scale provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. To quantify the de-bonding levels, the supervised learning-based statistical pattern recognition was implemented by composing a two-dimensional (2D) plane using the damage indices extracted from the impedance and guided wave features.

• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.383-390
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• 2007

This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.169-178
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• 2019

Now a day, we can perform various predictions by applying machine learning, which is a field of artificial intelligence; however, the finding of best algorithm in the field is always the problem. This paper predicts monthly power trading amount, monthly power trading amount of money, monthly index of production extension, final consumption of energy, and diesel for automotive using machine learning supervised algorithms. Then, we find most fit algorithm among them for each case. To do this we show the probability of predicting the value for monthly power trading amount and monthly power trading amount of money, monthly index of production extension, final consumption of energy, and diesel for automotive. Then, we try to average each predicting values. Finally, we confirm which algorithm is the most superior algorithm among them.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.37-46
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• 2007

The authentication in WSN(Wireless Sensor Network) usually means the entity authentication, but owing to the data centric nature of sensor network, much more importance must be put on the authentication(or attestation) for code of sensor nodes. The naive approach to the attestation is for the verifier to compare the previously known memory contents of the target node with the actual memory contents in the target node, but it has a significant drawback. In this paper, we show what the drawback is and propose a countermeasure. This scheme can verify the whole memory space of the target node and provides extremely low probability of malicious code's concealment without depending on accurate timing information unlike SWATT. We provide two modes of this verification method: BS-to-node and node-to-node. The performance estimation in various environments is shown.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.194-202
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• 2021

Ionosphere, one of the largest error sources, can pose potentially harmful threat to single-frequency GNSS (global navigation satellite system) user even after applying ionospheric corrections to their GNSS measurements. To quantitatively assess ionospheric impacts on the satellite navigation-based applications using simulation, the standard deviation of residual ionospheric errors is needed. Thus, in this paper, we determine conservative statistical quantity that covers typical residual ionospheric errors for nominal days. Extensive data-processing computes TEC (total electron content) estimates from GNSS measurements collected from the Korean reference station networks. We use Klobuchar model as a correction to calculate residual ionospheric errors from TEC (total electron content) estimate. Finally, an exponential delay model for residual ionospheric errors is presented as a function of local time and satellite elevation angle.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.13-20
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• 2019

Recently, object detection technology based on CNN has been actively studied. Object detection technology is used as an important technology in autonomous vehicles, intelligent image analysis, and so on. In this paper, we propose a rotation change robust object detection system by applying MI-FL (Moment Invariant-Feature Layer) to SSD (Single Shot Multibox Detector) which is one of CNN-based object detectors. First, the features of the input image are extracted based on the VGG network. Then, a total of six feature layers are applied to generate bounding boxes by predicting the location and type of object. We then use the NMS algorithm to get the bounding box that is the most likely object. Once an object bounding box has been determined, the invariant moment feature of the corresponding region is extracted using MI-FL, and stored and learned in advance. In the detection process, it is possible to detect the rotated image more robust than the conventional method by using the previously stored moment invariant feature information. The performance improvement of about 4 ~ 5% was confirmed by comparing SSD with existing SSD and MI-FL.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.9-16
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• 2019

Companies that want to improve their manufacturing processes have recently introduced the smart factory, which is particularly noticeable. The ultimate goal is to maximize the area of the smart factory that performs the process of the production facility completely with minimal manual control and to minimize errors of reasoning. This research is a part of a project for unmanned production, management, packaging, and delivery management and the detection of the start point of rebars to perform the automatic calibration of the rollers through the tracking of the automated facilities of unmanned production. It must meet the requirement to accurately track the position from the start point to the end point. In order to improve the tracking performance, it is important to set the accurate start point. However, the probability of tracking errors is high depending on environments such as illumination and dust through the conventional time-based detection method. In this paper, we propose a starting point detection method using the average brightness change of high speed IR camera to reduce the errors according to the environments, As a result, its performance is improved by more than 15%.