• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.104-113
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• 2006

The main objective of this study is to investigate the effect of compounded welding by using acoustic emission (AE) signals and doing a source location for weld heat affected zone (HAZ) through tensile testing. This study was carried out an SWS 490A high strength steel for electric shield metal arc welding, SMAW; $CO_2$ gas metal arc welding, GMAW($CO_2$); and gas tungsten arc welding, GTAW/TIG. Data displays are based on the measured parameters of the AE signals, along with environmental variables such as time and load. For instance, Gutenberg-Richter magnitude-frequency relationship (G-R MFR) offers useful b-value in data analysis. Namely event identification, source location gives the X- and Y-coordinates of the AE source. And K-means clustering analysis by Euclidean distance confirmed that was powerful to source location. Generally, strength of welded metal zone was stronger than strength of base metal. As the result, confirmed certainly that fracture is produced in HAZ instead of welded metal zone from source location.

• International Journal of Industrial Entomology and Biomaterials
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• v.31 no.2
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• pp.115-126
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• 2015

The tropical climate prevailing in India adversely affects temperate bivoltine silkworm rearing and causes crop loss especially during summer. Identification of high temperature tolerant bivoltine breeds by screening for thermotolerance in the silkworm, Bombyx mori (Lepidoptera: Bombycidae) is an essential prerequisite for the development of thermotolerant bivoltine breeds / hybrids. Therefore, in this study, 20 silkworm breeds were reared at different temperatures (25 ± 1℃,32 ± 1℃, 34 ± 1℃ and 36 ± 1℃) for 6 h every day from 3^rd d of 5^th instar to till spinning. Significant differences (p < 0.01) were found among all the rearing traits over temperature. Based on pupation percentage, SK4C and BHR3 were identified as thermotolerant bivoltine breeds. Hierarchical clustering analysis based on rearing traits at tested temperatures grouped 20 silkworm breeds in four clusters which included one cluster each of susceptible and tolerant, and two clusters of moderately tolerant silkworm breeds. This suggests that clustering based on rearing data at high temperatures by using Euclidean distance can be an effective approach in classifying the silkworm breeds on their thermotolerance capacity. The identified breeds would be used for development of thermo tolerant bivoltine silkworm breeds / hybrids.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.95-102
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• 2006

This paper proposes the KB-Fano algorithm which has lower decoding complexity by applying modified Fano-like metric bias to the conventional K-best algorithm. Additionally, an efficient K-best decoding algorithm, named the KR-Fano scheme, is proposed by jointly combining the K-reduction and the KB-Fano schemes. Simulations show that the proposed algerian provides the remarkable improvement from the viewpoints of the BER performance and the decoding complexity as compared to the conventional K-best scheme.

• Journal of Sensor Science and Technology
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• v.24 no.4
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• pp.258-263
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• 2015

In order to prevent drink-driving by detecting concentration of alcohol from driver's exhale breath, twenty chemical sensors fabricated. The one of purposes for sensor array which consists of those sensors is to discriminate between target gas(alcohol) and interference gases($CH_3CH_2OH$, CO, NOx, Toluene, and Xylene). Wilks's lambda was presented to achieve above purpose and optimal sensors were selected using the method. In this paper, step-wise sensor elimination based on Euclidean distance was investigated for selecting optimal sensors and compared with a result of Wilks's lambda method. The selectivity and sensitivity of sensor array were used for comparing performance of sensor array as a result of two methods. The data acquired from selected sensor were analyzed by pattern analysis methods, principal component analysis and Sammon's mapping to analyze cluster tendency in the low space (2D). The sensor array by stepwise sensor elimination method had a better sensitivity and selectivity compared to a result of Wilks's lambda method.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.257-264
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• 2005

This paper suggests a heuristic algorithm for the clustering problem. Clustering involves grouping similar objects into a cluster. Clustering is used in a wide variety of fields including data mining, marketing, and biology. Until now there are a lot of approaches using Self-Organizing Feature Maps(SOFMs). But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of k output-layer nodes, if they want to make k clusters. This approach has problems to classify elaboratively. This paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We can find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. We use the well known IRIS data as an experimental data. Unsupervised clustering of IRIS data typically results in 15 - 17 clustering error. However, the proposed algorithm has only six clustering errors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.586-589
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• 2013

In this paper, the proposed scheme is STBC system combined with convolutional code to ensure the reliability of data transmission for a high rate wireless communication. In addition, this scheme uses a modified viterbi algorithm in order to get a high system gain when data is transmitted. Because we combine STBC and comvolutional code, the proposed scheme can get a diversity gain of STBC and coding gain of convolutional code at the same time. Unlike existing viterbi docoding algorithm using Hamming distance in order to calculate branch matrix, the modified viterbi algorithm uses Euclidean distance value between received symbol and reference symbol. To analyze the system proposed, it was simulated by changing the constraint length of the convolutional code and the number of transmit and receive antennas of STBC.

• Development and Reproduction
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• v.23 no.4
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• pp.377-384
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• 2019

Genomic DNA extracted from representatives of two populations, Gunsan and Chinese, of Urechis spp. was amplified using PCR with several primers. The band-sharing (BS) value between individuals no. 05 from the Gunsan population and no. 22 from the Chinese population was 0.206, which was the lowest recognized value. Oligonucleotides primer OPC-04 revealed 44 unique loci, which distinguished the Chinese population. Primer OPB-17 allowed the discovery of 22 loci shared by the two populations, which were present in all samples. Based on the average BS results, individuals from the Gunsan population demonstrated lower BS values (0.661±0.012) than did those from the Chinese population (0.788±0.014; p<0.05). The shortest genetic distance (GD) displaying a noteworthy molecular difference was between individuals CHINESE no. 12 and no. 13 (GD=0.027). Individual no. 06 from the Gunsan population was most distantly related to CHINESE no. 22 (GD=0.703). A group tree of the two populations was constructed by UPGMA Euclidean GD analysis based on a total of 543 fragments generated using six primers. The explicit markers recognized in this study will be used for genetic analysis, as well as to evaluate the species security and proliferation of echiuran individuals in intertidal regions of the Korean Peninsula.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.403-409
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• 2012

This paper proposes an energy efficient ECG monitoring system by putting some intelligence on the sensor node to reduce the number of transmissions. The sensor node is mostly put into the processing mode and just connects the base station when necessary. Therefore, the transmission energy is greatly reduced while the energy for processing is increased a little bit. Our proposed ECG analysis method classifies ECG cycles by computing the Euclidean distance between the sensed ECG cycle and the reference ECG cycle. This work is a detailed and full explanation of our former work. Extended experimental results show that the proposed trade is very effective in saving energy and the Euclidean distance based classification method is accurate. Furthermore, the PowerTOSSIM energy simulation method is also demonstrated as very accurate in evaluating the energy consumption of the sensor node in our application scenario.