• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1165-1171
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• 2017

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup due to vectorization as a function of the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size to achieve vector efficiency greater than 90%. When the execution times for events are allowed to vary, the vector speedup is also limited by differences in the execution time for events being carried out in a single event-iteration.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2655-2663
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• 1993

In order to evaluate the relative significance of tolerance management of various elements in a VHS VTR tape transport system, the effect of geometric variations of the elements from standard design values on the tape traveling path is studied. The tape is modeled as a string and each element in the tape transport system is modeled as a cylinder whose radius, position vector and orientation vector are specified. An numerical algorithm is proposed to find the coordinates of tape entry points and tape exit points for the elements from which the tape traveling path can be completely described. By using the suggested algorithm, an error sensitivity analysis of tape traveling path due to the geometric variations of tape transport elements is performed for a particular model in the market and the elements demanding relatively strict tolerance management are identified.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.179-183
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• 2006

As there are many human activities in the coastal regions, various facilities and coastal engineering structures for protecting beach have been built. Dredging work, reclamation and harbor construction have caused the topography of sea floor to change rapidly. So sedimentation in the vicinity of the groins has get dull and the serious aspects sometimes turn up. Analyzing the surface sediments with transport vector model is one of the good methods to understand the sedimentation in the vicinity of the groins. I analyzed the transport vector of the surface sediments in the vicinity of the groins at the region where serious beach erosion happens near Pohang harbor.

• Journal of the Korean Ceramic Society
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• v.28 no.11
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• pp.878-884
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• 1991

The mobility and diffusivity in an edge dislocation in an FCC crystal formed by the removal of one half of a (100) plane were evaluated in an applied field by analyzing a vacancy tight binding model using Stark's matrix technique. A model of an edge dislocation in an FCC crystal was constructed for a [100] Burgers vector where vacancy transport along the edge dislocation in an FCC crystal was constructed for a [100] Burgers vector where vacancy transport along the edge of the extrac half plane of ions was considered. The model considered a tight binding approximation of the vacancy to the compressed region of the core and carried the calculation to the limit of an infinite length of dislocation. The diffusivity and the ratio of mobility to diffusivity were found to increase without bounds in the limit where the correlation factor becomes zero. In contrast, as the correlation factor became unity, the diffusivity became zero and the ratio of mobility to diffusivity became unity associated with the uncorrelated limit of 1/kT. This implied that the phenomenon was not unique to the crystal structure but was unique to edge dislocations with vacancy tight binding.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.6
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• pp.540-552
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• 2008

We predicted to seasonal sediment transport pathway of the estuary area of the Nakdong river using the STA method. The eCSedtrend model was used to flexible application of the previous STA methods. The analysis of the seasonal interpretation of sediment transport pathway showed that the most dominant trend in the Nakdong estuary was CB+ and CB-. In case of CB+, it was identified around the area where the mud sediment was distributed and formed transport vector toward the north. Also, in case of CB-, it was identified mostly around the sand bar where the sand sediment was distributed and generally showed transport vector toward the north even though there was seasonal difference.

• Journal of Korea Trade
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• v.25 no.1
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• pp.18-33
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• 2021

Purpose - This paper investigates the causal relationship between logistics infrastructure development and the economic growth of Korea. Considering the industrial and economic structure of Korea, it is likely that logistics infrastructure is positively associated with the economic growth of the country. Design/methodology - The causal relationship between logistics infrastructure and economic development is estimated using Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) considering long-run equilibrium between the two factors. To this end, a dataset consisting of 7 logistics infrastructure proxies and 5 economic growth indicators covering the period of 1990-2017 is used. Findings - It was found that causality, in general, runs from logistics infrastructure development to economic growth. Specifically, the results indicate that maritime transport is positively associated with the economic growth of Korea in terms of GDP and international trade. In addition, other modes of transport also have a positive impact on either the GDP or international trade of Korea. Originality/value - While existing studies in this area are based on either regional observations or a specific mode of transport, this study presents empirical evidence on causality between logistics infrastructure and the economic growth of Korea using a more comprehensive dataset. In addition, the findings in this paper can provide valuable implications for transport infrastructure development policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.2 s.10
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• pp.1-10
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• 2006

In this paper, VTS(Vector Taylor Series) algorithm, which was proposed by Moreno at Carnegie Mellon University in 1996, is analyzed and simulated. VTS is considered to be one of the robust speech recognition techniques where model parameter conversion technique is adapted. To evaluation performance of the VTS algorithm, We used CMN(Cepstral Mean Normalization) technique which is one of the well-known noise processing methods. And the recognition rate is evaluated when white gaussian and street noise are employed as background noise. Also, the simulation result is analyzed in order to be compared with the previous one which was performed by Moreno.

• Korea Trade Review
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• v.47 no.2
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• pp.69-88
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• 2022

This paper aims to predict Busan's regional product and employment using the logistic regression models and machine learning models. The following are the main findings of the empirical analysis. First, the OLS regression model shows that the main industries such as electricity and electronics, machine and transport, and finance and insurance affect the Busan's income positively. Second, the binomial logistic regression models show that the Busan's strategic industries such as the future transport machinery, life-care, and smart marine industries contribute on the Busan's income in large order. Third, the multinomial logistic regression models show that the Korea's main industries such as the precise machinery, transport equipment, and machinery influence the Busan's economy positively. And Korea's exports and the depreciation can affect Busan's economy more positively at the higher employment level. Fourth, the voting ensemble model show the higher predictive power than artificial neural network model and support vector machine models. Furthermore, the gradient boosting model and the random forest show the higher predictive power than the voting model in large order.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.84-90
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• 2011

In this paper, a VoIP-based voice secure telecommunication technology using the text-independent speaker authentication in the telematics environments is proposed. For the secure telecommunication, the sender's voice packets are encrypted by the public-key generated from the speaker's voice information and submitted to the receiver. It is constructed to resist against the man-in-the middle attack. At the receiver side, voice features extracted from the received voice packets are compared with the reference voice-key received from the sender side for the speaker authentication. To improve the accuracy of text-independent speaker authentication, Gaussian Mixture Model(GMM)-supervectors are applied to Support Vector Machine (SVM) kernel using Bayesian information criterion (BIC) and Mahalanobis distance (MD).

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.9-16
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• 2023

The natural language on social network platforms has a certain front-to-back dependency in structure, and the direct conversion of Chinese text into a vector makes the dimensionality very high, thereby resulting in the low accuracy of existing text classification methods. To this end, this study establishes a deep learning model that combines a big data ultra-deep convolutional neural network (UDCNN) and long short-term memory network (LSTM). The deep structure of UDCNN is used to extract the features of text vector classification. The LSTM stores historical information to extract the context dependency of long texts, and word embedding is introduced to convert the text into low-dimensional vectors. Experiments are conducted on the social network platforms Sogou corpus and the University HowNet Chinese corpus. The research results show that compared with CNN + rand, LSTM, and other models, the neural network deep learning hybrid model can effectively improve the accuracy of text classification.