• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.225-233
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• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.43-50
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• 2016

In this paper, we propose the protocol of Ethernet that will receive a popular interesting in the automotive intelligent network, it also attempts to implementation and verification through simulation and experiments to propose a fault tolerance algorithm when the data transfer on it. It has proven the usefulness of the system in order to apply toward an existing automotive communication system. In the case of actual real-time data for automotive industry, we generated a randomly-generated data which is the set of payload into a standard format to complete the experiment. Among the implemented existing algorithms performance, we confirmed the effectiveness of all range from a single data to mixed (Hybrid-type) data, to verify the proposed algorithm.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.13-28
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• 2018

The ministry of Environment of Korea initiated two follow-up surveys in 2005 and 2006 to investigate environmental effect on children's health. These two cohorts, referred to as the 2005 Cohort and 2006 Cohort, were followed up three times every two years. This data set was referred to as the Children's Health and Environmental Research (CHEER) data set. This paper reproduces the existing research results of Kim et al. (Journal of the Korean Data and Information Science Society, 25, 987-998, 2014) and Lee et al. (The Korean Journal of Applied Statistics, 29, 1295-1310, 2016) and derive a benchmark dose lower limit (BMDL) for blood lead level for attention deficit hyperactivity disorder (ADHD) after pooling two cohort data sets. The different ADHD rating scales were unified by applying the conversion formula proposed by Lee et al. (2016). The random effect model and AR(1) model were built to reflect the longitudinal characteristics and regression to the mean phenomenon. Based on these models the BMDLs for blood lead levels were derived using the BMDL formula and the simulation. We obtained a hight level of BMDLs when we pooled two independent cohort data sets.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1194-1204
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• 2023

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b^*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b^*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.4
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• pp.447-451
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• 2012

The objective of this research was to determine the prevalence, risk factors and consequent effect of dystocia on lactation performance in Holstein dairy cows in Iran. The data set consisted of 55,577 calving records on 30,879 Holstein cows in 30 dairy herds for the period March 2000 to April 2009. Factors affecting dystocia were analyzed using multivariable logistic regression models through the maximum likelihood method in the GENMOD procedure. The effect of dystocia on lactation performance and factors affecting calf birth weight were analyzed using mixed linear model in the MIXED procedure. The average incidence of dystocia was 10.8% and the mean (SD) calf birth weight was 42.13 (5.42) kg. Primiparous cows had calves with lower body weight and were more likely to require assistance at parturition (p<0.05). Female calves had lower body weight, and had a lower odds ratio for dystocia than male calves (p<0.05). Twins had lower birth weight, and had a higher odds ratio for dystocia than singletons (p<0.05). Cows which gave birth to a calf with higher weight at birth experienced more calving difficulty (OR (95% CI) = 1.1(1.08-1.11). Total 305-d milk, fat and protein yield was 135 (23), 3.16 (0.80) and 6.52 (1.01) kg less, in cows that experienced dystocia at calving compared with those that did not (p<0.05).

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.64-71
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• 2010

Recently, to achieve high performance of the processor, the cache is splits physically into two parts, one for instruction and one for data. This paper proposes an architecture of asynchronous instruction cache based on mixed-delay model that are DI(delay-insensitive) model for cache hit and Bundled delay model for cache miss. We synthesized the instruction cache at gate-level and constructed a test platform with 32-bit embedded processor EISC to evaluate performance. The cache communicates with the main memory and CPU using 4-phase hand-shake protocol. It has a 8-KB, 4-way set associative memory that employs Pseudo-LRU replacement algorithm. As the results, the designed cache shows 99% cache hit ratio and reduced latency to 68% tested on the platform with MI bench mark programs.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.24-29
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• 2003

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing schemes, which represents the information from observations as a set of random variables in the from of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other. which can be utilized in linear projection.. However, it has been known that ICA does not establish good performance in source separation by itself. Thus, in order to overcome this limitation, there have been many techniques that are designed to reinforce the good properties of ICA, which improves the mixed image separation. Unfortunately, the innovation process still needs to be studied since it yields inconsistent innovation process that is attached to the ICA, the expectation and maximization process is added. The results presented in this paper show that the proposed improves the image separation as presented in experiments.

• Korean Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.1-19
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• 1996

Non-manifold topological representations can provide a single unified representation for mixed dimensional models or cellular models and thus have a great potential to be applied in many application areas. Various boundary representations for non-manifold topology have been proposed in recent years. These representations are mainly interested in describing the sufficient adjacency relationships and too redundant as a result. A model stored in these representations occupies too much storage space and is hard to be manipulated. In this paper, we proposed a compact hierarchical non-manifold boundary representation that is extended from the half-edge data structure for solid models by introducing the partial topological entities to represent some non-manifold conditions around a vertex, edge or face. This representation allows to reduce the redundancy of the existing schemes while full topological adjacencies are still derived without the loss of efficiency. To verify the statement above, the storage size requirement of the representation is compared with other existing representations and present some main procedures for querying and traversing the representation. We have also implemented a set of the generalized Euler operators that satisfy the Euler-Poincare formula for non-manifold geometric models.

• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.111-111
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• 2022

According to data from the Ministry of Environment, food waste accounted for 27% of the nation5 s household waste in 2020, and 4.67 million tons of food waste is being discharged per year. According to the Food Waste Direct Landfill Prohibition Act, food waste must be incinerated, composted, fodder, and decomposed before landfilling. The cost of incineration and landfilling of food waste is considerable. Therefore, through the process of turning food waste into fertilizer, we are going to investigate the limit of crop application and the change in the growth of crops during continuous use of food waste fertilizer. This study investigated the growth of lettuce such as shoot length, root length, leaf number, fresh weight, and dry weight after treating lettuce with food waste dry powder mixed fertilizer. The experiment was carried out continuously in 2021 (1st year) and 2022 (2nd year), and the treatment groups were set to No Treatment (NT), Chemical Fertilizer (CF), Mixed Fertilizer (MF×1), and Mixed Fertilizer×2 (MF×2), was repeated 3 times. As a result of the 1st year growth survey, there was no significant difference between NT and CF in the case of shoot length, but MF×1 and MF×2 were significantly decreased compared to NT. Root length was not significantly different in all treatment groups. As for the leaf number, there was no significant difference between NT and MF×1, but CF and MF×2 were significantly decreased compared to NT. In fresh weight, MF×1 and MF×2 were significantly decreased compared to NT, and in the case of dry weight, there was no significant difference between NT, MF×1, and MF×2. As a result of the 2nd year growth survey, there was a significant difference in CF and MF×2 in leaf number, but there was no significant difference in all treatment groups with respect to shoot length, root length, fresh weight, and dry weight. Through continuous additional research, it is necessary to confirm the change in soil composition and the growth of crops due to food waste fertilizer treatment.