• Food Science of Animal Resources
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• v.43 no.2
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• pp.282-304
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• 2023

This study aimed to investigate the effectiveness of carotenoid supplementation on the performance, egg quality, and immunity of laying hens using a meta-analysis approach. The database was searched using Google Scholar and Scopus, from 2012 to 2022. The literature was published in English. 47 Articles were selected for meta-analysis. Analyses were performed using the Open Meta-analyst for Ecology and Evolution (OpenMEE) software. The heterogeneity and data validation against publication bias were analyzed using JASP 0.16.2 software. Overall, the results showed that carotenoid supplementation improved feed intake by 0.32 g/day/hen [95% confidence interval (CI)=0.02 to 0.61], final body weight by 0.33 g/hen (95% CI=0.05 to 0.60), egg production by 0.38% (95% CI=0.14 to 0.63), egg weight by 0.29 g (95% CI=0.09 to 0.5), yolk colour by 2.11 (95% CI=1.71 to 2.51), Haugh unit (HU) by 0.26 (95% CI=0.11 to 0.42), yolk carotenoids by 1.17 ㎍/kg (95% CI=0.59 to 1.75), immunoglobulin A (IgA) by 0.74 mg/L (95% CI=0.18 to 1.29), and lower yolk cholesterol by -0.38 mg/g (95% CI=-0.59 to -0.16). Feed conversion ratio (FCR), eggshell thickness, and white blood cells were unaffected by the application of carotenoids. The heterogeneity analysis showed variability in all studies (<0.05). In conclusion, carotenoid supplementation can elevate productivity, enhance egg quality, and improve immunity. However, based on Kendall's test, there was a publication bias in several parameters, namely FCR, egg weight, HU, yolk carotenoids, and IgA.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.97-103
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• 2022

An aircraft component can only be mounted on an aircraft if it has been certified to have a structural robustness under flight load conditions. Among the major components of the aircraft, a pylon is a structure that connects external equipment such as an engine, and external attachments with the main wing of an aircraft and transmits the loads acting on it to the main structure of the aircraft. In civil aircraft, when there is an incident of fire in the engine area, the pylon prevents the fire from spreading to the wings. This study presents the results of structural static tests performed to verify the structural robustness of a fuel pylon used to mount external fuel tank in an aircraft. In the main text, we present the test set-up diagram consisting of test fixture, hydraulic pressure unit, load control system, and data acquisition equipment used in the structure static test of the fuel pylon. In addition, we introduce the software that controls the load actuator, and provide a test profile for each test load condition. As a result of the structural static test, it was found that the load actuator was properly controlled within the allowable error range in each test, and the reliability of the numerical analysis was verified by comparing the numerical analysis results and the strain obtained from the structural test at the main positions of the test specimen. In conclusion, it was proved that the fuel pylon covered in this study has sufficient structural strength for the required load conditions through structural static tests.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5802-5809
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• 2015

Railway signaling system is the vital control system in charge of the core for safely train operation, its functional safety must be checked through sufficient verification. Until now, to verify the interoperability of developed railway signaling system, the on-site testing approaches have been applied after testing in laboratory with simulator. This approaches are some limited range of interoperable verification, so more systematic verification interoperability is required. In this paper, the three phases of interoperability verification for railway signaling system was proposed, and methodology for each phases are represented. And also The interoperability validation methodology and supported testing tool for railway signaling system is represented in this paper

• Geomechanics and Engineering
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• v.28 no.5
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• pp.521-529
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• 2022

This research work deals with the development of air pluviation method for preparing uniform sand specimens for conducting large scale laboratory testing. Simulating real field conditions and to get reliable results, air pluviation method is highly desirable. This paper presents a special technique called air pluviation or sand raining technique for achieving uniform relative density. The apparatus is accompanied by a hopper, shutters with different orifice sizes and numbers and set of sieves. Before using this apparatus, calibration curves are drawn for relative density against different height of fall (H) and shutter sizes. From these calibration curves, corresponding to the desired relative density of 60%, the shutter size of 13mm and height of fall of 457.2 mm, are selected and maintained throughout the pluviation process. The density obtained from the mobile pluviator is then verified using the Dynamic Cone Penetrometer (DCP) test where the soil is poured in the box using defined shutter size and fall height. The results obtained from the DCP test are averaged as 60±0.5 which was desirable. The mobile pluviator used in this research is also capable of obtaining relative densities up to 90%. The instrument is validated using experimental and numerical approach. In numerical study, Plaxis 3D software is used in which the soil mass is defined by 10-Node tetrahedral elements and 6-Node plate is used to simulate plate behavior in the validation phase. The results obtained from numerical approach were compared with that of experimental one which showed very close correlation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.43-52
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• 2023

Rubber produced by rubber companies is subjected to quality suitability inspection through rheometer test, followed by secondary processing for automobile parts. However, rheometer test is being conducted by humans and has the disadvantage of being very dependent on experts. In order to solve this problem, this paper proposes a deep learning-based rheometer quality inspection system. The proposed system combines LSTM(Long Short-Term Memory) and CNN(Convolutional Neural Network) to take advantage of temporal and spatial characteristics from the rheometer. Next, combination materials of each rubber was used as an auxiliary input to enable quality conformity inspection of various rubber products in one model. The proposed method examined its performance with 30,000 validation datasets. As a result, an F1-score of 0.9940 was achieved on average, and its excellence was proved.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.485-496
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• 2022

This study is for the software implementation to generate atmospheric and surface reflectance products from RapidEye satellite imagery. The software is an extension based on Orfeo Toolbox (OTB) and an open-source remote sensing software including calibration modules which use an absolute atmospheric correction algorithm. In order to verify the performance of the program, the accuracy of the product was validated by a test image on the Radiometric Calibration Network (RadCalNet) site. In addition, the accuracy of the surface reflectance product generated from the KOMPSAT-3A image, the surface reflectance of Landsat Analysis Ready Data (ARD) of the same site, and near acquisition date were compared with RapidEye-based one. At the same time, a comparative study was carried out with the processing results using QUick Atmospheric Correction (QUAC) and Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) tool supported by a commercial tool for the same image. Similar to the KOMPSAT-3A-based surface reflectance product, the results obtained from RapidEye Extension showed accuracy of agreement level within 5%, compared with RadCalNet data. They also showed better accuracy in all band images than the results using QUAC or FLAASH tool. As the importance of the Red-Edge band in agriculture, forests, and the environment applications is being emphasized, it is expected that the utilization of the surface reflectance products of RapidEye images produced using this program will also increase.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.235-240
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• 2006

The paper will give an overview of the mission of GalTeC and then concentrate on two main aspects. The first more detailed aspect, is the analysis of the key performance parameters for the Galileo system services and presenting a technical overview of methods and algorithms used. The second more detailed aspect, is the service volume prediction including service dimensioning using the Prediction tool. In order to monitor and validate the Galileo SIS performance for Open Service (OS) and Safety Of Life services (SOL) regarding the key performance parameters, different analyses in the SIS domain and User domain are considered. In the SIS domain, the validation of Signal-in-Space Accuracy SISA and Signal-in-Space Monitoring Accuracy SISMA is performed. For this purpose first of all an independent OD&TS and Integrity determination and processing software is developed to generate the key reference performance parameters named as SISRE (Signal In Space Reference Errors) and related over-bounding statistical information SISRA (Signal In Space Reference Accuracy) based on raw measurements from independent sites (e.g. IGS), Galileo Ground Sensor Stations (GSS) or an own regional monitoring network. Secondly, the differences of orbits and satellite clock corrections between Galileo broadcast ephemeris and the precise reference ephemeris generated by GalTeC will also be compared to check the SIS accuracy. Thirdly, in the user domain, SIS based navigation solution PVT on reference sites using Galileo broadcast ephemeris and the precise ephemeris generated by GalTeC are also used to check key performance parameters. In order to demonstrate the GalTeC performance and the methods mentioned above, the paper presents an initial test result using GPS raw data and GPS broadcast ephemeris. In the tests, some Galileo typical performance parameters are used for GPS system. For example, the maximum URA for one day for one GPS satellite from GPS broadcast ephemeris is used as substitution of SISA to check GPS ephemeris accuracy. Using GalTeC OD&TS and GPS raw data from IGS reference sites, a 10 cm-level of precise orbit determination can be reached. Based on these precise GPS orbits from GalTeC, monitoring and validation of GPS performance can be achieved with a high confidence level. It can be concluded that one of the GalTeC missions is to provide the capability to assess Galileo and general GNSS performance and prediction methods based on a regional and global monitoring networks. Some capability, of which first results are shown in the paper, will be demonstrated further during the planned Galileo IOV phase, the Full Galileo constellation phase and for the different services particularly the Open Services and the Safety Of Life services based on the Galileo Integrity concept.

• Advances in concrete construction
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• v.9 no.3
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• pp.235-248
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• 2020

Progressive collapse in a structure occurs when load bearing members are failed and the adjoining structural elements cannot resist the redistributed forces and fails subsequently, that leads to complete collapse of structure. Recently, construction using precast concrete technology is adopted increasingly because it offers many advantages like faster construction, less requirement of skilled labours at site, reduced formwork and scaffolding, massive production with reduced amount of construction waste, better quality and better surface finishing as compared to conventional reinforced concrete construction. Connections are the critical elements for any precast structure, because in past, major collapse of precast structure took place because of connection failure. In this study, behavior of four different precast wet connections with U shaped reinforcement bars provided at different locations is evaluated. Reduced 1/3^rd scale precast beam column assemblies having two span beam and three columns with removed middle column are constructed and examined by performing experiments. The response of precast connections is compared with monolithic connection, under column removal scenario. The connection region of test specimens are filled by cast-in-place micro concrete with and without polypropylene fibers. Performance of specimen is evaluated on the basis of ultimate load carrying capacity, maximum deflection at the location of removed middle column, crack formation and failure propagation. Further, Finite element (FE) analysis is carried out for validation of experimental studies and understanding the performance of structural components. Monolithic and precast beam column assemblies are modeled using non-linear Finite Element (FE) analysis based software ABAQUS. Actual experimental conditions are simulated using appropriate boundary and loading conditions. Finite Element simulation results in terms of load versus deflection are compared with that of experimental study. The nonlinear FE analysis results shows good agreement with experimental results.