• Journal of Animal Science and Technology
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• v.58 no.6
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• pp.19.1-19.7
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• 2016

Background: Cowpea (Vigna unguiculata [L.]) is a legume cultivated throughout most tropical countries and is valued as food and feed for human and livestock respectively. The search for an improved cowpea variety has been on-going with the aim of improving traits such as grain yield, drought and pest resistance. But no information exist on the feeding value of these improved varieties. Phosphate (P) fertilizer application is recommended to augment grain yield in grain legumes but data on the effect of P fertilizer on haulm quality is limited. Results: Two separate experiments were conducted to determine the effect of P fertilizer dose on the nutritive value of haulms from different cowpea varieties (V). In experiment 1, effect of three P doses (30, 60 and 90 kg $P_2O_5/ha$) on in vitro gas production (IVGP) characteristics, concentrations of digestible organic matter (DOM), crude protein (CP), acid detergent fiber (ADF) and neutral detergent fiber (NDF) of haulms from five cowpea varieties (Zaayura-SARC 4-75, Songotra-IT97K-499-35, Hewale-IT93K-192-4, IT99K 573-1-1 and Asomdwe-IT94K-410-2) were investigated using the $3(P){\times}5(V)$ factorial treatment arrangements in a completely randomized design. In experiment 2, the effects of two P doses (30 and 90 kg $P_2O_5/ha$) and two varieties (Zaayura-SARC 4-75 and Hewale-IT93K-192-4) on the voluntary feed intake, live weight, haematology and carcass characteristics of Djallonke lambs were also assessed using a $2(P){\times}2(V)$ factorial treatment arrangement. The $V{\times}P$ interaction significantly affected CP, NDF and ADF with CP concentration increasing with increase in P doses in Zaayura-SARC 4-75 and Asomdwe-IT94K-410-2. Whilst an increase (P < 0.05) in NDF was observed in Songotra-IT97K-499-35and Asomdwe-IT94K-410-2 as P doses increased, the other V only increased from P dose 30 to 60 kg/ha and declined at P dose 90 kg/ha. The ADF decreased (P < 0.05) with increase in P dose for all V with the exception of Songotra-IT97K-499-35. There was a significant V effect on DOM with the highest reported in Zaayura-SARC 4-75 (43.44 %). Daily DM intake, carcass length and blood urea nitrogen of the lambs were significantly affected by the V x P interaction. There was a significant V effect on globulin and P effect on live weight at slaughter, dressed weight, chuck, leg, loin, rib and flank and liver and lungs. Conclusion: It can be concluded that nutrient concentrations of cowpea haulms were positively influenced by different P dose and varieties with favorable effects on growth, haematology and carcass composition of lambs. Varieties Zaayura-SARC 4-75 and Hewale-IT93K-192-4 at P dose at 90 kg/ha are recommended to enhance growth performance and carcass yield of Djallonke lambs.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• Fire Science and Engineering
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• v.23 no.3
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• pp.40-47
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• 2009

Nowadays the diversity and large-capacity of electric appliances are strong effect on electrical fires augment in an alarming way. But, as the inactive response characteristics of the existing RCD (Residual Current protective Device) used on low voltage power distribution system, so control of overload and electric short circuit faults, major causes of electrical fires, are not enough. Therefore, this paper is confirmed the unreliability of the existing RCD by electrical fault simulator and is proposed a Electrical Fire Disaster Prevention Device (EFDPD) by using a high precision current sensor (namely, reed switch) for the prevention of electrical disasters in low voltage power distribution system caused by overload or electric short circuit faults. The sensitive reed switch in the proposed EFDPD exactly detects the increased magnetic flux with the overload or the short current caused by a number of electrical faults, and the following, the EFDPD has double protection function which operates self circuit breaker or rapidly cuts off the existing RCD. The proposed EFDPD is confirmed the excellent characteristics in response velocity and accuracy in comparison with the conventional circuit breaker through various operation performance analysis. The proposed EFDPD can also prevent electrical disaster, like as electrical fires, which resulted from the malfunction and inactive response characteristics of the existing RCD.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.43-54
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• 2019

In this paper, we review the applicability of fog screen to implement 'Spatial Augmented Reality' which displays the image on the whole space of real space or in real space by separating display equipment and user, in contrast to the traditional Augmented Reality. Through three exhibitions and one performance, we confirmed t hat the fog screen, which can be passed through, is a suitable material for implementing the Spatial Augment ed Reality. We found that the hologram production was easier than before because of fog screen. Through the questionnaire survey conducted on performers along with the exhibition, we found that only about half of people know what a fog screen is, and about 10% of the total respondents saw the fog screen. In order to investigate the effect of fog screen on the surrounding space, we conducted an experiment to observe the change of humidity according to the time and distance in the Children's Culture Center of the Asian Culture Center. We found that the humidity within a radius of 5m around the fog screen could increase by 2~3%($6,400m^3$ standard). Thus we provided some safety requirement with fog screen when works made of materials vulnerable to moisture such as paint, paper, and wood are exhibited at the same time with fog screen in the exhibition hall.

• Journal of the Korean Recycled Construction Resources Institute
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• v.6 no.4
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• pp.311-318
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• 2018

When reinforced concrete structures are exposed to fire, their mechanical properties such as compressive strength, elasticity coefficient and rebar yield strength, are degraded. Therefore, the structure's damage assessment is essential in determining whether to dismantle or augment the structure after a fire. In this study, the confinement effect of lateral reinforcement of RC column according to the numbers of fire exposure face and stirrup was verified by fire resistant test with the heating temperatures of $400^{\circ}C$, $600^{\circ}C$ and $800^{\circ}C$. The test results showed that the peak stress decreases and peak strain increases as the temperature is getting higher, also transverse ties are helpful in improving the compressive resistance of concrete subjected to high temperature. Based on the results of this study, the residual stress of confined concrete under thermal damage is higher at the condition of more lateral reinforcement ratio and less fire exposure faces. The decreasing ratio of elastic modulus of more confined and less exposure faces from the relationship of load and displacement was also smaller than that of opposite conditions.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.61-66
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• 2019

Augmented reality is a technology that makes a virtual object appear as if it exists in reality by composing a virtual object in real time with the image captured by the camera. In order to augment the virtual object on the object existing in reality, the homography of images utilized to estimate the position and orientation of the object. The homography can be estimated by applying the RANSAC algorithm to the feature points of the images. But the homography estimation method using the RANSAC algorithm has a problem that accurate homography can not be estimated when there are many feature points in the background. In this paper, we propose a method to filter feature points of a background when the object is near and the background is relatively far away. First, we classified the depth image into relatively near region and a distant region using the Otsu's method and improve homography estimation performance by filtering feature points on the relatively distant area. As a result of experiment, processing time is shortened 71.7% compared to a conventional homography estimation method, and the number of iterations of the RANSAC algorithm was reduced 69.4%, and Inlier rate was increased 16.9%.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.