• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1540-1549
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• 2017

Objective: Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods: We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results: We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion: The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1127-1136
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• 2021

In the field of power analysis attacks, electrical noise and misalignment of the power consumption trace are the major factors that determine the success of the attack. Therefore, several studies have been conducted to overcome this problem, and one of them is a signal processing method based on wavelet transform. Up to now, discrete wavelet transform, which can compress the trace, has been mostly used for power side-channel power analysis because continuous wavelet transform techniques increase data size and analysis time, and there is no efficient scale selection method. In this paper, we propose an efficient scale selection method optimized for power analysis attacks. Furthermore, we show that the analysis performance can be greatly improved when using the proposed method. As a result of the CPA(Correlation Power Analysis) and DDLA(Differential Deep Learning Analysis) experiments, which are non-profiling attacks, we confirmed that the proposed method is effective for noise reduction and trace alignment.

• Korean Journal of Organic Agriculture
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• v.28 no.2
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• pp.189-208
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• 2020

The purpose of this study aims to estimate consumption selection attribute, part-worth of organic instant rice through the use of conjoint analysis method. The conjoint analysis is to trace the development of consumer preference among multi-attribute alternatives. The selection attribute was including 4 factors preferred Type of rice, Capacity, Brand and payment price. For this research, a total of 192 questionnaires was collected of which 200 were completed. The research design was a full profile method by orthogonal design then 9 main profiles, 3 holdout sets were created. The results of this research were as follows. Consumers of organic instant rice are consider their importance of selection attributes was in order to price (25.87%), Type of rice (27.231%), Brand/Purchase channel (24.013%) and Capacity (18.494%). The findings of this study have identified 3 clusters for each experience visitors. Each cluster has a different and showed the relative importance or preference values for each accessible attribute of the segmentation.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.73-82
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• 1996

Vehicle movement detection by high order correlation analysis of optical sensor array signals is introduced. The optical sensors observe the road which is assumed to be a non-uniform speckle-like texture. The measurement system is applicable to general robotic movement detection because : 1) It employs a non-contact measurement method, 2) The system can be made very compact, and 3) It enables approximation of the movement trace with a sequence of arcs instead of the conventional connection of simple line segments. In this work, we have looked into estimation of running trace of an autonomous vehicle by observing the ground pattern.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.15-23
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• 2017

Template attack is a powerful side-channel analysis technique which can be performed by an attacker who has a test device that is identical to target device. Template attack is consisted of building template in profiling phase and matching the target device using template that were calculated in profiling phase. One methods to improve the success rate of template attack is to better estimate template which is consisted sample mean and sample covariance matrix of gaussian distribution in template profiling. However restriction of power trace in profiling phase led to poor template estimation. In this paper, we propose new method to select noisy power trace in profiling phase. By eliminating noisy power trace in profiling phase, we can construct more advanced mean and covariance matrix which relates to better performance in template attack. We proved that the proposed method is valid through experiments.

• Bulletin of the Korean Chemical Society
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• v.20 no.10
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• pp.1165-1171
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• 1999

The analysis of trace herbicides using the on-line SPE-HPLC system and a photochemical reaction was studied. 18 compounds of herbicides including eight triazines, six phenoxy acids and esters, and four other herbicides were examined. The on-line SPE-HPLC system developed for selection of eluting solvent improved chromatographic efficiency. The recoveries of herbicides were higher than 77%. With 100 mL tap water samples, the detection limits for all analytes were in the 0.1-2.3×10-10 M range. Detection was done by a UV or fluorescence spectrometer after photochemical reaction at the end of the column with 2W or 450W mercury lamp. Without a photochemical reaction, all compounds responded to 230 nm UV detector, but phenoxy acids and esters were weakly detected. However, with a photochemical reaction, these compounds were selectively detected at 320 nm wavelength of UV absorption and 400 nm emission of the fluorescence detectors. This method can be used for the analysis of environmental water containing herbicides at trace levels.

• Genomics & Informatics
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• v.20 no.4
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• pp.48.1-48.7
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• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.131-138
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• 2022

A Mobile Ad-hoc Network (MANET) is a collection of moving nodes that communicate and collaborate without relying on a pre-existing infrastructure. In this type of network, nodes can freely move in any direction. Routing in this sort of network has always been problematic because of the mobility of nodes. Most existing protocols use simple routing algorithms and criteria, while another important criterion is path selection. The existing protocols should be optimized to resolve these deficiencies. 'Particle Swarm Optimization (PSO)' is an influenced method as it resembles the social behavior of a flock of birds. Genetic algorithms (GA) are search algorithms that use natural selection and genetic principles. This paper applies these optimization models to the OLSR routing protocol and compares their performances across different metrics and varying node sizes. The experimental analysis shows that the Genetic Algorithm is better compared to PSO. The comparison was carried out with the help of the simulation tool NS2, NAM (Network Animator), and xgraph, which was used to create the graphs from the trace files.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1271-1280
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• 2020

The yield and quality of a micromanufacturing process are important management factors. In real-world situations, it is difficult to achieve a high yield from a manufacturing process because the products are produced through multiple nanoscale manufacturing processes. Therefore, it is necessary to identify the processes and equipment that lead to low yields. This paper proposes an analytical method to identify the processes and equipment that cause a defect in the plastic ball grid array (PBGA) during the manufacturing process using logistic regression and stepwise variable selection. The proposed method was tested with the lot trace records of a real work site. The records included the sequence of equipment that the lot had passed through and the number of faults of each type in the lot. We demonstrated that the test results reflect the real situation in a PBGA manufacturing process, and the major equipment parameters were then controlled to confirm the improvement in yield; the yield improved by approximately 20%.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.9-11
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• 2010

Multiple-input multiple-output (MIMO) systems assisted by multi-relays with single antenna are considered. Signal transmission consists of two hops. In the first hop, the source node broadcasts the vector symbols to all relays, then all relays forward the received signals multiplied by each power gain to the destination simultaneously. Unlike the case of full cooperation between relays such as single relay with multiple antennas, in our case there is no closed form solution for optimal relay power gain with respect to minimum mean square error (MMSE). Thus we propose an alternative approach in which we use an approximation of the cost function based on rank-one matrix decomposition. As a cost function, we choose the trace of MSE matrix. We give several simulation results to validate that our proposed method obtains a negligible performance loss compared to optimal solution obtained by exhaustive search.