• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.21 no.3
• /
• pp.427-435
• /
• 1997

Conditional sampling techniques are utilized to investigate the relation between the wall skin-friction and stream wise velocity fluctuations in a turbulent boundary layer. Conditionally averaged results using a peak detection and the VITA (variable-interval time-averaging) technique show that a high skin friction is associated with high frequency components of the wall skin-friction fluctuations. The conditionally averaged wall skin-friction fluctuations obtained by using the VITA technique have a positively-skewed characteristics compared with the conditionally averaged stream wise velocity fluctuations. It is confirmed that there exists a phase shift between the wall skin-friction and stream wise velocity fluctuations, which was also found from the long-time averaged space-time correlations. The amount of phase shift between the wall skin-friction and stream wise velocity fluctuations is the same as that from the long-time averaged space-time correlations and does not change despite the variation of the detection threshold.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.11
• /
• pp.1299-1307
• /
• 2014

In this work, an appropriate analysis model of a precise foot sensor with low detection pressure capability under a low range of variation in the dimensional variables was proposed. With a simple two-dimensional model, it was found that a remarkably high error level sometimes occurred between the analysis and experimental results. In order to overcome the error and improve the performance, a three-dimensional model was introduced, and the detection pressure and sensor characteristics were compared with those of the experimental results, which showed its enhanced performance with less error and higher precision.

• Journal of Korean Institute of Industrial Engineers
• /
• v.28 no.2
• /
• pp.147-161
• /
• 2002

In novelty detection, one attempts to discriminate abnormal patterns from normal ones. Novelty detection is quite difficult since, unlike usual two class classification problems, only normal patterns are available for training. Auto-Associative Multi-Layer Perceptron (AAMLP) has been shown to provide a good performance based upon the property that novel patterns usually have larger auto-associative errors. In this paper, we give a mathematical analysis of 2-layer AAMLP's output characteristics and empirical results of 2-layer and 4-layer AAMLPs. Various activation functions such as linear, saturated linear and sigmoid are compared. The 2-layer AAMLPs cannot identify non-linear boundaries while the 4-layer ones can. When the data distribution is multi-modal, then an ensemble of AAMLPs, each of which is trained with pre-clustered data is required. This paper contributes to understanding of AAMLP networks and leads to practical recommendations regarding its use.

• Journal of Korea Multimedia Society
• /
• v.14 no.6
• /
• pp.719-729
• /
• 2011

This paper presents a research on the fast and accurate method of line detection in the image of a wireless mobile robot (WMR). For the improvement of the processing time to detect lines, the characteristics of the transmitted image from the WMR was analyzed, and the efficient preprocessing method among the existing preprocessing methods was selected. And for the improvement of the accuracy to detect lines, the selection method of local maximum value at the Hough array (HA) which has the result of Hough transform was improved by designing a mask and applying it to HA. The experiment was performed with acquired images from the WMR, and the proposed method outperformed the existing methods in terms of processing time and line detection.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.11
• /
• pp.2191-2203
• /
• 2011

In this paper, we propose a fast and robust algorithm for fighting behavior detection based on Motion Vectors (MV), in order to solve the problem of low speed and weak robustness in traditional fighting behavior detection. Firstly, we analyze the characteristics of fighting scenes and activities, and then use motion estimation algorithm based on block-matching to calculate MV of motion regions. Secondly, we extract features from magnitudes and directions of MV, and normalize these features by using Joint Gaussian Membership Function, and then fuse these features by using weighted arithmetic average method. Finally, we present the conception of Average Maximum Violence Index (AMVI) to judge the fighting behavior in surveillance scenes. Experiments show that the new algorithm achieves high speed and strong robustness for fighting behavior detection in surveillance scenes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.705-712
• /
• 2004

In this paper, detection of rotor position at standstill of toroidal switched reluctance motor(TSRM) with built-in search coils using neural network is proposed. When search coils are used as a position sensor, it has many advantages like low cost, decrease in the volume, high robust characteristics and wide applications. However, the initial rotor position detection is very difficult because the search coil's EMF doesn't exist at standstill. In this paper, detection of initial rotor position of TSRM with built-in search coils using neural network is suggested. The experiment for the proposed method are presented. As a result of that, the accuracy and validity of the proposed method is verified.

• Smart Structures and Systems
• /
• v.20 no.2
• /
• pp.219-229
• /
• 2017

Outlier detection is an imperative task to identify the occurrence of abnormal events before the structures are suffered from sudden failure during their service lives. This paper proposes a two-phase method for the outlier detection of Global Positioning System (GPS) monitoring data. Prompt judgment of the occurrence of abnormal data is firstly carried out by use of the relational analysis as the relationship among the data obtained from the adjacent locations following a certain rule. Then, a negative selection algorithm (NSA) is adopted for further accurate localization of the abnormal data. To reduce the computation cost in the NSA, an improved scheme by integrating the adjustable radius into the training stage is designed and implemented. Numerical simulations and experimental verifications demonstrate that the proposed method is encouraging compared with the original method in the aspects of efficiency and reliability. This method is only based on the monitoring data without the requirement of the engineer expertise on the structural operational characteristics, which can be easily embedded in a software system for the continuous and reliable monitoring of civil infrastructure.

• Journal of Sensor Science and Technology
• /
• v.17 no.1
• /
• pp.15-22
• /
• 2008

When designing image sensors including a CMOS vision chip for edge detection, resolution is a significant factor to evaluate the performance. It is hard to improve the resolution of a bio-inspired CMOS vision using a resistive network because the vision chip contains many circuits such as a resistive network and several signal processing circuits as well as photocircuits of general image sensors such as CMOS image sensor (CIS). Low resolution restricts the use of the application systems. In this paper, we improve the resolution through layout and circuit optimization. Furthermore, we have designed a printed circuit board using FPGA which controls the vision chip. The vision chip for edge detection has been designed and fabricated by using $0.35{\mu}m$ double-poly four-metal CMOS technology, and its output characteristics have been investigated.

• The Plant Pathology Journal
• /
• v.30 no.1
• /
• pp.96-101
• /
• 2014

The molecular features of Pseudomonas syringae pv. actinidiae strains isolated in Korea were compared with strains isolated in Japan and Italy. Sequencing of eight P. syringae pv. actinidiae and three P. syringae pv. theae strains revealed a total of 44 single nucleotide polymorphisms across 4,818 bp of the concatenated alignment of nine genes. A multiplex PCR assay was developed for the detection of P. syringae pv. actinidiae and for the specific detection of recent haplotype strains other than strains isolated since the 1980s in Korea. The primer pair, designated as TacF and TacR, specifically amplified a 545-bp fragment with the genomic DNA of new haplotype of P. syringae pv. actinidiae strains. A multiplex PCR conducted with the TacF/TacR primer pair and the universal primer pair for all P. syringae pv. actinidiae strains can be simultaneously applied for the detection of P. syringae pv. actinidiae and for the differentiation of new haplotype strains.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.9
• /
• pp.935-942
• /
• 2009

In this paper, the purpose is to investigate the natural frequency of a cracked Timoshenko cantilever beams by FEM(finite element method) and experiment. In addition, a method for detection of crack in a cantilever beams is presented based on natural frequency measurements. The governing differential equations of a Timoshenko beam are derived via Hamilton's principle. The two coupled governing differential equations are reduced to one fourth order ordinary differential equation in terms of the flexural displacement. The crack is assumed to be in the first mode of fracture and to be always opened during the vibrations. The detection method of a crack location in a beam based on the frequency measurements is extended here to Timoshenko beams, taking the effects of both the shear deformation and the rotational inertia into account. The differences between the actual and predicted crack positions and sizes are less than 6 % and 23 % respectively.