• Animal Bioscience
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• v.36 no.11
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• pp.1700-1708
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• 2023

Objective: The objective of this study was to determine the effects of β-mannanase on metabolizable energy (ME) and apparent total tract digestibility (ATTD) of protein in various feedstuffs including barley, copra meal, corn, corn distillers dried grains with solubles (DDGS), palm kernel meal, sorghum, and soybean meal. Methods: A basal diet was formulated with 94.8% corn and 0.77% amino acids, minerals, and vitamins and test diets replacing corn-basal diets with barley, corn DDGS, sorghum, soybean meal, or wheat (50%, respectively) and copra meal or palm kernel meal (30%, respectively). The basal diet and test diets were evaluated by using triplicated or quadruplicated 2×2 Latin square designs consisting of 2 diets and 2 periods with a total of 54 barrows at 20.6±0.6 kg (9 wk of age). Dietary treatments were levels of β-mannanase supplementation (0 or 800 U/kg of feed). Fecal and urine samples were collected for 4 d following a 4-d adaptation period. The ME and ATTD of crude protein (CP) in feedstuffs were calculated by a difference procedure. Data were analyzed using Proc general linear model of SAS. Results: Supplementation of β-mannanase improved (p<0.05) ME of barley (10.4%), palm kernel meal (12.4%), sorghum (6.0%), and soybean meal (2.9%) fed to growing pigs. Supplementation of β-mannanase increased (p<0.05) ATTD of CP in palm kernel meal (8.8%) and tended to increase (p = 0.061) ATTD of CP in copra meal (18.0%) fed to growing pigs. Conclusion: This study indicates that various factors such as the structure and the amount of β-mannans, water binding capacity, and the level of resistant starch vary among feedstuffs and the efficacy of supplemental β-mannanase may be influenced by these factors.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.68-77
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• 2008

We have developed an inversion algorithm for loop-loop electromagnetic (EM) data, based on the localised non-linear or extended Born approximation to the solution of the 2.5D integral equation describing an EM scattering problem. Source and receiver configuration may be horizontal co-planar (HCP) or vertical co-planar (VCP). Both multi-frequency and multi-separation data can be incorporated. Our inversion code runs on a PC platform without heavy computational load. For the sake of stable and high-resolution performance of the inversion, we implemented an algorithm determining an optimum spatially varying Lagrangian multiplier as a function of sensitivity distribution, through parameter resolution matrix and Backus-Gilbert spread function analysis. Considering that the different source-receiver orientation characteristics cause inconsistent sensitivities to the resistivity structure in simultaneous inversion of HCP and VCP data, which affects the stability and resolution of the inversion result, we adapted a weighting scheme based on the variances of misfits between the measured and calculated datasets. The accuracy of the modelling code that we have developed has been proven over the frequency, conductivity, and geometric ranges typically used in a loop-loop EM system through comparison with 2.5D finite-element modelling results. We first applied the inversion to synthetic data, from a model with resistive as well as conductive inhomogeneities embedded in a homogeneous half-space, to validate its performance. Applying the inversion to field data and comparing the result with that of dc resistivity data, we conclude that the newly developed algorithm provides a reasonable image of the subsurface.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.5
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• pp.315-323
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• 2015

Damage level of coastal structures has been scaled up according to increase of wave height and duration of the storm due to the abnormal global climate change. So, the design criteria for new breakwaters is being intensified and structural strengthening is also conducted for the existing breakwaters. Recently, interlocking concept has been much attention to enhance the structural stability of the conventional caisson structure designed individually to resist waves. The interlocking caisson breakwater may be survival even if unusual high wave occurs because the maximum wave force may be reduced by phase lags among the wave forces acting on each caisson. In this study, the dispersion characteristics of wave forces using interlocking system that connect the upper part of caisson with cable in the normal direction of breakwater was investigated. A simplified linear model was developed for computational efficiency, in which the foundation and connection cables were modelled as linear springs, and caisson structures were assumed to be rigid. From numerical experiments, it can be found that the higher wave forces are transmitted through the cable as the angle of incident wave is larger, and the larger the stiffness of the interlocking cable makes larger wave dispersion effect.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.17-30
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• 2002

Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.64-73
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• 2020

As Korean government and safety-related organizations make continuous efforts to reduce the number of industrial accidents, accident rate has steadily declined since 2010, thereby recording 0.48% in 2017. However, the number of fatalities due to industrial accidents was 1,987 in 2017, which means that more efforts should be made to reduce the number of industrial accidents. As an essential activity for enhancing the system safety, accident analysis can be effectively used for reducing the number of industrial accidents. Accident analysis aims to understand the process of an accident scenario and to identify the plausible causes of the accident. Accident analysis offers useful information for developing measures for preventing the recurrence of an accident or its similar accidents. However, it seems that the current practice of accident analysis in Korean manufacturing companies takes a simplistic accident model, which is based on a linear and deterministic cause-effect relation. Considering the actual complexities underlying accidents, this would be problematic; it could be more significant in the case of human error-related accidents. Accordingly, it is necessary to use a more elaborated accident model for addressing the complexity and nature of human-error related accidents more systematically. Regarding this, HFACS(Human Factors Analysis and Classification System) can be a viable accident analysis method. It is based on the Swiss cheese model and offers a range of causal factors of a human error-related accident, some of which can be judged as the plausible causes of an accident. HFACS has been widely used in several work domains(e.g. aviation and rail industry) and can be effectively used in Korean industries. However, as HFACS was originally developed in aviation industry, the taxonomy of causal factors may not be easily applied to accidents in Korean industries, particularly manufacturing companies. In addition, the typical characteristics of Korean industries need to be reflected as well. With this issue in mind, we developed HFACS-K as a method for analyzing accidents happening in Korean industries. This paper reports the process of developing HFACS-K, the structure and contents of HFACS-K, and a case study for demonstrating its usefulness.

• Land and Housing Review
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• v.2 no.3
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• pp.287-297
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• 2011

This paper presents the results of performance verification tests of the isolated flat plate apartment building with the laminated rubber bearings. The shaking table test is carried out in CABR(China Academy of Building Research) with two 1/10 scale isolation and non-isolation models under 4 excitation waves. The shaking table test is proceeding from x axis, y axis and x+y axis with different amplitude of acceleration values. The results show that, to non-isolated model, the natural vibration period is remarkably decreased and entered non-linear condition after moderate earthquake. Its accelerations become lager with increasing storey number and completely collapsed under large earthquake. The inter-storey shifts largely exceed the limit values of regulated displacement angles. But to isolated model, the natural vibration period of isolated modal is almost the same in all conditions and still in its elastic condition. The earthquake loading is greatly reduced and the accelerations of superstructure are greatly reduced. The inter-storey drifts are very small and can be neglected. The isolated model is in translational state and can be seen as a rigid whole. The displacements of isolation layer are in the allowable range. This experiment demonstrates that the seismic isolation is very effective to mitigate the influence of earthquake on structures and it is possible to increase the serviceability due to decrease the floor acceleration. facilities from their good states that is superior to non-isolated structure.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.335-347
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• 2013

In February 2008, high storm waves due to a developed atmospheric low pressure system propagating from the west off Hokkaido, Japan, to the south and southwest throughout the East Sea (ES) caused extensive damages along the central coast of Japan and along the east coast of Korea. This study consists of two parts. In the first part, we estimate extreme storm wave characteristics in the Toyama Bay where heavy coastal damages occurred, using a non-hydrostatic meteorological model and a spectral wave model by considering the extreme conditions for two factors for wind wave growth, such as wind intensity and duration. The estimated extreme significant wave height and corresponding wave period were 6.78 m and 18.28 sec, respectively, at the Fushiki Toyama. In the second part, we perform numerical experiments on wave-structure interaction in the Fushiki Port, Toyama Bay, where the long North-Breakwater was heavily damaged by the storm waves in February 2008. The experiments are conducted using a non-linear shallow-water equation model with adaptive mesh refinement (AMR) and wet-dry scheme. The estimated extreme storm waves of 6.78 m and 18.28 sec are used for incident wave profile. The results show that the Fushiki Port would be overtopped and flooded by extreme storm waves if the North-Breakwater does not function properly after being damaged. Also the storm waves would overtop seawalls and sidewalls of the Manyou Pier behind the North-Breakwater. The results also depict that refined meshes by AMR method with wet-dry scheme applied capture the coastline and coastal structure well while keeping the computational load efficiently.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.561-573
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• 2023

National forests have an advantage over private forests in terms of higher investment in capital, technology, and labor, allowing for more intensive management. As such, national forests are expected to serve not only as a strategic reserve of forest resources to address the long-term demand for timber but also to stably perform various essential forest functions demanded by society. However, most forest stands in the current national forests belong to the fourth age class or above, indicating an imminent timber harvesting period amid an imbalanced age class structure. Therefore, if timber harvesting is not conducted based on systematic management planning, it will become difficult to ensure the continuity of the national forests' diverse functions. This study was conducted to determine the optimal volume of timber production in the national forests to improve the age-class structure while sustainably maintaining their economic and public functions. To achieve this, the study first identified areas within the national forests suitable for timber production. Subsequently, a forest management planning model was developed using multi-objective linear programming, taking into account both the national forests' economic role and their public benefits. The findings suggest that approximately 488,000 hectares within the national forests are suitable for timber production. By focusing on management of these areas, it is possible to not only improve the age-class distribution but also to sustainably uphold the forests' public benefits. Furthermore, the potential volume of timber production from the national forests for the next 100 years would be around 2 million m³ per year, constituting about 44% of the annual domestic timber supply.