• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.5
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• pp.81-87
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• 2012

New car assessment program (NCAP) originated from USNCAP in 1979 has been implemented in several countries or markets, for instance USA, Europe, Korea, Japan, China and Australia. NCAP has contributed greatly to reduce accidental tolls. But recently, NCAP performance has no distinction between cars because manufacturer have been continuously developed to improve NCAP performance. Therefore, NHTSA announced new USNCAP protocol becoming effective from MY2011. NHTSA had carried out many NCAP tests based on the new test protocol and announced these test results. In this paper, USNCAP test results were reviewed by statistical method. This review was focused on passenger cars and frontal crash test results in order to investigate effect of changes in new NCAP protocol. There are two key changes, one is sited female dummy in passenger position, the other is enlarged to 4 scoring body regions in each dummy. Results of this review were summarized as followings. Performance in Passenger (12.5%) is lower than Driver's (50%) for number of 5 star vehicle. Neck injury criterion is dominant to NCAP star rating for both dummies in the mean sense. For standard deviation, chest deflection is showed largest value in driver dummy but neck injury criterion is showed for passenger's. DKAB and PKAB were equipped 28.1% and 6.2%, respectively. Consequently, the countermeasure for new USNCAP frontal crash test is essential to control well dummy kinematics with some safety features including KAB to reduce neck injuries.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.12
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• pp.985-991
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• 2014

The combined method utilizing airborne LiDAR and GIS data is suggested to extract 3-dimensional hybrid city model including roads and buildings. Combining the two types of data is more efficient to estimate the elevations of various types of roads and buildings than using either LiDAR or GIS data only. This method is particularly useful to model the overlapped roads around the so called spaghetti junction. The preliminary model is constructed from the LiDAR data, which can give wrong information around the overlapped parts. And then, the erratic vertex points are detected by imposing maximum vertical grade allowable on the elevated roads. For the purpose of efficiency, the erratic vertex points are corrected through linear interpolation method. To avoid the erratic treatment of the LiDAR data on the facades of buildings 2 meter inner-buffer zone is proposed to efficiently estimate the height of a building. It is validated by the mean value(=5.26 %) of differences between estimated elevations on 2 m inner buffer zone and randomly observed building elevations.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.61-69
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• 2014

Collaborative filtering recommendation creates similar item subset or similar user subset based on user preference about items and predict user preference to particular item by using them. Thus, if preference matrix has low density, reliability of recommendation will be sharply decreased. To solve these problems we suggest Hybrid Preference Prediction Technique Using Weighting based Data Reliability. Preference prediction is carried out by creating similar item subset and similar user subset and predicting user preference by each subset and merging each predictive value by weighting point applying model condition. According to this technique, we can increase accuracy of user preference prediction and implement recommendation system which can provide highly reliable recommendation when density of preference matrix is low. Efficiency of this system is verified by Mean Absolute Error. Proposed technique shows average 21.7% improvement than Hao Ji's technique when preference matrix sparsity is more than 84% through experiment.

• Safety and Health at Work
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• v.13 no.3
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• pp.326-335
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• 2022

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

• Steel and Composite Structures
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• v.45 no.2
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.1
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• pp.55-58
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• 2000

Germination of sweet and super sweet corn is lower than normal corn due to the higher sugar and lower starch contents of kernels. Sweet corn seeds are easily deteriorated in the field under the unfavorable condition, therefore it is important to identify the optimal harvesting time for seed production. This trial was conducted to investigate the responses of germination percentage of shrunken-2(sh2), brittle(bt), sugary(su), and sugary enhancer(se) hybrids in relation to harvesting dates. Eight hybrids of four different gene sweet corns were harvested at 15, 20, 25, 30, 35, 40, 45, and 50 days after silking(DAS). Germination test was performed using paper towel method. Mean germination percentages across eight hybrids showed the highest value at 45 DAS. There were significant differences among genes and within gene for germination. Shrunken-2 hybrid Mecca was higher than su hybrids for germination, indicating that sh2 would not be poorer than su Late harvesting beyond the optimal harvesting date might not be desirable because of more lodging and ear rots. Theoretical optimal harvesting date estimated from the regression equation was 40.9 DAS, however, practical date for harvesting would be a few days later than the estimated date if seedling vigor might be considered. Kernel dry weight per ear showed similar response to germination. Regression equation showed the highest kernel dry weight at 40.7 DAS. Significant correlations between kernel dry weight and germination were observed, impling that kernel dry matter accumulation would be an important factor for germination.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.9
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• pp.703-712
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• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub-and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of unbalance and resonance which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.1
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• pp.1-17
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• 2013

The investigation for species composition and catch in the Korean deep-water of the East Sea (also known as Sea of Japan) was carried out with trammel nets of 7 mesh sizes (6.1~24.2cm) offshore Donghae (2006) and Yangyang (2007) of Korea. The catches were 1,268kg and composed of 37 species between 200m and 1,200m in depth. The principal species caught were Taknka's snailfish, salmon snailfish, red snow crab, hunchback sculpin, snow crab, spinyhead sculpin, Tanaka's eelpout, Alaska cod and so on. Those were target fish for commercial value except salmon snailfish. The mesh sizes for the largest catch were 10.6cm and 15.2cm in the fishing ground of Donghae and Yangyang, respectively. The habitat of snow crab was shallower than that of red snow crab in both areas. Trammel net enabled to investigate fish in deep-water with small fishing vessel and rather cheap expenses in contrast to bottom trawl that required too much of it. With increasing inner mesh size of trammel net the mean size of some principal species such as Taknka's snailfish, spinyhead sculpin, hunchback sculpin, Pacific cod, snow crab, red snow crab and hybrid between snow crab and red snow crab tended to be large in certain range of mesh size.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.4
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• pp.317-320
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• 2001

Sweet com seeds deteriorate faster due to low starch content than field com seeds when stored for a long tenn. This study had been conducted to observe the seed deterioration of four different sweet corns in a long tenn storage conditions in room temperature. Four kinds of sweet com genes (sh2, bt, su, and se) were harvested from 15 days to 50 days after silking with 5-day intervals. These seeds were stored in the room temperature and tested for germination percentages from 3 months to 18 months period with 3-month interval. su seeds germinated better than other types of gene. Hybrid Mecca which is sh2 gene germinated better when stored for 3 months to 18 months. For all genes, mean regression equations in relation to storage periods showed linear responses. For regression equation, the slope of sh2 gene was lower than that of su gene. The highest slope value was observed in bt gene showing faster deterioration rate. The rate at which seed deteriorates seems to be affected by the date at which it was harvested. The seeds that were harvested at the optimum time deteriorated more slowly than those which were not.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5392-5418
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• 2017

The primary aim of this paper is to propose a non-linear regression based technique for mapping different network Quality of Service (QoS) factors to an integrated end-user Quality of Experience (QoE) or Mean Opinion Score (MOS) value for an online video streaming service on a mobile phone. We use six network QoS factors for finding out the user QoE. The contribution of this paper is threefold. First, we investigate the impact of the network QoS factors on the perceived video quality. Next, we perform an individual mapping of the significant network QoS parameters obtained in stage 1 to the user QoE based upon a non-linear regression method. The optimal QoS to QoE mapping function is chosen based upon a decision variable. In the final stage, we evaluate the integrated QoE of the system by taking the combined effect of all the QoS factors considered. Extensive subjective tests comprising of over 50 people across a wide variety of video contents encoded with H.265/HEVC and VP9 codec have been conducted in order to gather the actual MOS data for the purpose of QoS to QoE mapping. Our proposed hybrid model has been validated against unseen data and reveals good prediction accuracy.