• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.10-20
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• 2019

Recently, fluidic thrust vector control has become a core technique to control multifarious air vehicles, such as supersonic aircraft and modern rockets. Fluidic thrust vector control using the shock vector concept has many advantages for achieving great vectoring performance, such as fast vectoring response, simple structure, and low weight. In this paper, computational fluid dynamics methods are used to study a three-dimensional rectangular supersonic nozzle with a slot injector. To evaluate the reliability and stability of computational methodology, the numerical results were validated with experimental data. The pressure distributions along the upper and lower nozzle walls in the symmetry plane showed an excellent match with the test results. Several numerical simulations were performed based on the shear stress transport(SST) $k-{\omega}$ turbulence model. The effect of the momentum flux ratio was investigated thoroughly, and the performance variations have been clearly illustrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Journal of Biosystems Engineering
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• v.36 no.1
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• pp.40-47
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• 2011

Image analysis algorithm for the quality evaluation of ginseng seedling was investigated. The images of ginseng seedling were acquired with a color CCD camera and processed with the image analysis methods, such as binary conversion, labeling, and thinning. The processed images were used to calculate the length and weight of ginseng seedlings. The length and weight of the samples could be predicted with standard errors of 0.343 mm, and 0.0214 g respectively, $R^2$ values of 0.8738 and 0.9835 respectively. For the evaluation of the three quality grades of Gab, Eul, and abnormal ginseng seedlings, features from the processed images were extracted. The features combined with the ratio of the lengths and areas of the ginseng seedlings efficiently differentiate the abnormal shapes from the normal ones of the samples. The grade levels were evaluated with an efficient pattern recognition method of support vector machine analysis. The quality grade of ginseng seedling could be evaluated with an accuracy of 95% and 97% for training and validation, respectively. The result indicates that color image analysis with support vector machine algorithm has good potential to be used for the development of an automatic sorting system for ginseng seedling.

• Korean Journal of Veterinary Research
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• v.39 no.4
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• pp.786-796
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• 1999

As an attempt to develop an effective control method against theileriosis, recombinant antigen protein was produced. Thirty-two kDa membrane protein(MP) gene of T sergenti was amplified through RT-PCR from extracted total RNA of T sergenti isolated in Chonbuk, Korea. The amplified 869 bp of Korean T sergenti membrane gene was cloned and the base sequences were analyzed. The amplified gene was cloned into E coli expression vector, pQE32 plasmid vector, and the vector was introduced into E coli strain M15 to produce the recombinant membrane protein. For the induction of T sergenti membrane protein(KTs-MP), the plasmid harboring E coli strain M15 were cultured in the presence of IPTG, and the recombinant protein were purified by $Ni^+$-NTA agarose. Then, to confirm the authenticity of the produced membrane protein, molecular weight of expressed recombinant KTs-MP was analyzed by SDS-PAGE and Western blotting. The molecular weight of expressed recombinant protein was 32 kDa as expected. The recombinant KTs-MP was successfully recognized by anti-His Tag antibody, antisera of T sergenti infected cattle and monoclonal antibody of T sergenti membrane protein. Therefore, we concluded that the authentic 32 kDa membrane protein of T sergenti was produced as immunologically recognizable form.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.837-852
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• 2021

Recurrent neural network (RNN) architectures have been used for language modeling (LM) tasks that require learning long-range word or character sequences. However, the RNN architecture is still suffered from unstable gradients on long-range sequences. To address the issue of long-range sequences, an attention mechanism has been used, showing state-of-the-art (SOTA) performance in all LM tasks. A differentiable neural computer (DNC) is a deep learning architecture using an attention mechanism. The DNC architecture is a neural network augmented with a content-addressable external memory. However, in the write operation, some information unrelated to the input word remains in memory. Moreover, DNCs have been found to perform poorly with low numbers of weight parameters. Therefore, we propose a robust memory deallocation method using a limited retention vector. The limited retention vector determines whether the network increases or decreases its usage of information in external memory according to a threshold. We experimentally evaluate the robustness of a DNC implementing the proposed approach according to the size of the controller and external memory on the enwik8 LM task. When we decreased the number of weight parameters by 32.47%, the proposed DNC showed a low bits-per-character (BPC) degradation of 4.30%, demonstrating the effectiveness of our approach in language modeling tasks.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.198-210
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• 2016

This study firstly aims to estimate a leading-price of Jeju flounders with various price-classes by fish weight and secondly plans to provide policy implications of flounder purchase projects by understanding dynamic changes and interactions among flounder producer price-classes caused by price impulses in the market. This study applies an unit root test for stability of data, uses a Granger causality test to estimate the leading-price among producer prices by fish weight, employs the vector autoregressive model to analyze statistical impacts among t-1 variables used in models, and finally utilizes impulse response analyses and forecast error variance decomposition analyses to understand dynamic changes and interactions among change rates of the producer prices caused by price impulses in the market. The results of the study are as follows. Firstly, KPSS, PP, and ADF tests show that the change rate of Jeju flounder monthly producer prices by fish weight differentiated by logarithm is stable. Secondly, the Granger causality test presents that the change rate of the 1kg flounder producer price strongly leads it of 500g, 700g, and 2kg flounder producer prices respectively. Thirdly, the vector autoregressive model indicates that the change rate of the 1kg producer price in t-1 period statistically, significantly influences it of own weight in t period and also slightly affects price change rates of other weights in t period. Fourthly, the impulse response analysis indicates that impulse responses of structural shocks for the change rate of the 1kg producer price are relatively more powerful in its own weight and in other weights than shocks emanating from price change rates of other weights. Fifthly, the variance decomposition analysis points out that the change rate of the 1kg producer price is relatively more influential than it of 500g, 700g, and 2kg producer prices respectively. In conclusion, the change rate of the 1kg Jeju flounder producer price leads the change rates of other ones and Jeju purchase projects need to be targeted to the 1kg Jeju flounder producer price as the purchase project implemented in 2014.

• Journal of the Korean Mathematical Society
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• v.55 no.3
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• pp.671-694
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• 2018

In this paper, we investigate the weighted vector-valued bounds for a class of multilinear singular integral operators, and its commutators, from $L^{p_1}(l^{q_1};\;{\mathbb{R}}^n,\;w_1){\times}{\cdots}{\times}L^{p_m}(l^{q_m};\;{\mathbb{R}}^n,\;w_m)$ to $L^p(l^q;\;{\mathbb{R}}^n,\;{\nu}_{\vec{w}})$, with $p_1,{\cdots},p_m$, $q_1,{\cdots},q_m{\in}(1,\;{\infty})$, $1/p=1/p_1+{\cdots}+1/p_m$, $1/q=1/q_1+{\cdots}+1/q_m$ and ${\vec{w}}=(w_1,{\cdots},w_m)$ a multiple $A_{\vec{P}}$ weights. Our argument also leads to the weighted weak type endpoint estimates for the commutators. As applications, we obtain some new weighted estimates for the $Calder{\acute{o}}n$ commutator.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.938-943
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• 1998

The induction motor of the electric vehicles is controlled based on the vector control method to obtain good torque control characteristics. In the conventional vector control system, the field exciting current should be kept on a constant value to keep a stable flux level. This method has a liability that core loss becomes increasing at the light load region. To solve this liability, the efficiency maximizing control method of the vector controlled induction motor is proposed in thid paper. We developed light weight water cooled 60kW induction motor drive system which adopts our method and fabricated a conversion electric car for actual vehicle test. We demonstrate the usefulness of drive system by comparing its driving mode with conventional field oriented system and an efficiency maximizing controlled induction motor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.866-871
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• 1994

B-spline curves and surfaces are effective solutions for design and modelling of the freeform models. The control methods of these are using with control points, knot vectors and weight of NURBS. Using control point is easy and resonable for representation of general models. But the movement of control points bring out the reformation of original convex hull. The B-splines with nonuniform knot vector provide good result of the shape modification without convex hull reforming. B-splines are constructed with control points and basis functions. Nonuniform knot vectors effect on the basis functions. And the blending curves describe the prorities of knot vectors. Applying of these, users will forecast of the reformed curves after modifying controllabler primitives.