• Korean Journal of Veterinary Service
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• v.35 no.4
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• pp.263-268
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• 2012

From the end of July 2012, several cases of abortion have been happened at the Korean indigenous cattle farm with 124 heads in Chungbuk province, Korea. Serological tests such as Rose-bengal test (RBT) and standard tube agglutination test (STAT) have been performed according to the standard official protocols of bovine brucellosis and 41 cattle turned out to be brucellosis-positive simultaneously. To find out the main factors of brucellosis outbreaks and spreads, additional serological, etiological and molecular investigation were applied. Totally, 11 B. abortus were isolated from 10 cattle's specimens including lymph-nodes and/or testis, and drinking water in cowhouse. In genotyping by multi-locus VNTR assay (MLVA) using 17 loci markers, the present B. abortus isolates were shown all the same pattern, D1 genotype, which has been reported in Gyeonggi and Gangwon province, Korea. These results suggest that the input of brucellosis might come from neighboring farms directly or indirectly, even if by unknown factor and expansion within farm would accelerate by materials related with aborting cows.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.88-95
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• 1996

It is inevitable for local systems to have deviations which represent interactions and modeling errors originated from the decomposition process of a large scale system. This paper presents a decentralized control scheme for interconnected systems using local linear models and a neuro-coordinator. In the proposed method, the local system is composed of a linear model and unknown deviations caused by linearizing the subsystems around operating points or by estimating parameters of the subsystems. Because the local system has unmeasurable deviations we define a local reference model which consists of a local linear model and a neural network to estimate the deviations indirectly. The reference model is reformed into a linear model which has no deviations through a transformation of input variables and we obtain an optimum feedback control law which minimizes a local performance index. Finally, we derive a decentralized feedback control law which consists of local linear states and neural network outputs. In the decentralized control, the neuro-coordinator generates a corrective control signal to cancel the effect of deviations through backpropagation learning with the errors obtained from the differences of the local system outputs and reference model outputs. Also, the stability of local system is proved by the degree of learning of the neural network under an assumption on a neural network learning index. It is shown by computer simulations that the proposed control scheme can be applied successfully to the control of a biased two-link planar robot manipulator.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.158-158
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• 2015

Myoblast are myogenic precursors that proliferate, activate, and differentiate on muscle injury to sustain the regenerative capacity of skeletal muscle; The neuronal isoform of nitric oxide synthase (nNOS, termed also NOS-I) is expressed in normal adult skeletal muscle, suggesting important functions for Nitric oxide (NO) in muscle biology1,2,3. However, the expression and subcellular localization of NO in muscle development and myoblast differentiation are largely unknown. In this study, we examined effects of the nitric oxide generated by a microwave plasma torch, on proliferation/differentiation of rat myoblastic L6 cells. Experimental data pertaining to nitric oxide production are presented in terms of the oxygen input in units of cubic centimetres per minute. The various levels of nitric oxide are observed depending on the flow rate of nitrogen gas, the ratio of oxygen gas, and the microwave power4. In order to evaluate the potential of nitric oxide as an activator of cell differentiation, we applied nitric oxide generated from the microwave plasma torch to L6 skeletal muscles. Differentiation of L6 cells into myotubes was significantly enhanced the differentiation after nitric oxide treatment. Nitric oxide treatment also increase the expression of myogenesis marker proteins and mRNA level, such as myogenin and myosin heavy chain (MHC), as well as cyclic guanosine monophosphate (cGMP), However during the myotube differentiation we found that NO activate oxidative stress signaling erks expression. Therefore, these results establish a role of NO and cGMP in regulating myoblast differentiation and elucidate their mechanism of action, providing a direct link with oxidative stress signalling, which is a key player in myogenesis. Based on these findings, nitric oxide generated by plasma can be used as a possible activator of cell differentiation and tissue regeneration.

• The Journal of Information Technology
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• v.7 no.4
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• pp.1-8
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• 2004

The depth information of 3D image lost by projecting 3D-object to 2D-screen for earning image. If depth information is restored and is used to recognize 3D-object, we can make the more effective recognition system. We often use shape from stereo algorithm in order to restore this information. In this paper, we suggest 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In this system, we use the moving vector of object to reduce matching time and In second matching step, the unknown input image is compared with the reference images, which is made with octree codes. Octree codes are used in volume-based representation of a three dimensional object. The result of simulation show that the proposed 3-D object recognition system provides satisfactory performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.573-582
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• 2020

Fuzzing is a method of testing software by randomly generating test cases. Since its introduction, a variety of fuzzing techniques have been studied. Among them, mutation-based fuzzing is an efficient method that finds real-world bugs even though it uses a simple approach such as probabilistic bit-flipping and character substitution. However, the interpreter fuzzing has difficulty in applying general mutation techniques because the interpreter requires grammar and semantic correctness input values. In this paper, we present a novel mutation-based fuzzing on JavaScript interpreters with a dynamic data flow analysis. To this end, we implement JMFuzzer that can generate various types of mutated test cases that operate normally without runtime errors in JavaScript interpreter considering syntax and semantics. As a result, we found numerous unknown vulnerabilities in the latest JavaScript interpreters. We reported all of them to the vendors.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.359-368
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• 2018

In this paper, a method is presented to identify the physical and modal parameters of multistory shear building based on substructural technique using block pulse generalized operational matrix and genetic algorithm. The substructure approach divides a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that identification processes can be independently conducted on each substructure. Block pulse functions are set of orthogonal functions that have been used in recent years as useful tools in signal characterization. Assuming that the input-outputs data of the system are known, their original BP coefficients can be calculated using numerical method. By using generalized BP operational matrices, substructural dynamic vibration equations can be converted into algebraic equations and based on BP coefficient for each story can be estimated. A cost function can be defined for each story based on original and estimated BP coefficients and physical parameters such as mass, stiffness and damping can be obtained by minimizing cost functions with genetic algorithm. Then, the modal parameters can be computed based on physical parameters. This method does not require that all floors are equipped with sensor simultaneously. To prove the validity, numerical simulation of a shear building excited by two different normally distributed random signals is presented. To evaluate the noise effect, measurement random white noise is added to the noise-free structural responses. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

• Ocean and Polar Research
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• v.25 no.1
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• pp.31-40
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• 2003

In August-September 2001, 15 samples of bottom sediments were collected in the inner, middle and open parts of Amursky Bay near Vladivostok, Russia, and barfin plaice Pleuronectes pinnifasciatus was sampled from the inner and the middle locations of the bay. In the sediments from all three sites elevated concentrations of several heavy metals, i.e. Zn ($102-115{\mu}/g$ dry weight), Ni $(70-73{\mu}g/g)$ and Cu $(27-35{\mu}g/g)$ were discovered. The contents of oil hydrocarbons were very close to or slightly higher than the maximal normal environmental background level, $100{\mu}g/g$ dry weight. The sediments contained negligible amounts of hexachlorocyclohexane, while DDT concentrations were quite high (1.7-16.3ng/g dry weight). Generally, there were no substantial differences in the pollution levels of the locations studied and our results resembled those reported for Amursky Bay in the 1990s. Surprisingly, in 2001 'fiesh' DDT comprised 70-85% of the total DDT content in sediment from all the locations studied. In fish liver total DDTs concentrations were 212.8 and 122.54 ng/g wet weight for the inner and the middle locations, respectively, and 'fresh' DDT comprised 35 and 64% of DDTs, respectively. These results provide evidence of recent input of DDT from an unknown source into the ecosystem of Amursky Bay. Histopathological changes revealed in the plaice liver (vacuolization of hepatocytes, coagulative necrosis of hepatocytes, inflammatory reaction, and necrosis of epithelial cells of bile ducts) are probably connected with an intensive metabolism of DDT in the fish organism. No histological and histomorphometric differences were found in the state of the interrenal tissue. Similar condition of the liver and the interrenal tissue in barfin plaice sampled from the inner and the middle locations of Amursky Bay may be explained by the absence of great differences in the pollution levels of these sites.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.45-51
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• 2011

In this paper, we propose an unsupervised learning method for modeling motion trajectory patterns effectively. In our approach, observations of an object on a trajectory are treated as words in a document for latent dirichlet allocation algorithm which is used for clustering words on the topic in natural language process. This allows clustering topics (e.g. go straight, turn left, turn right) effectively in complex scenes, such as crossroads. After this procedure, we learn patterns of word sequences in each cluster using Baum-Welch algorithm used to find the unknown parameters in a hidden markov model. Evaluation of abnormality can be done using forward algorithm by comparing learned sequence and input sequence. Results of experiments show that modeling of semantic region is robust against noise in various scene.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.265-271
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• 1992

It is the purpose of this paper to present a dialogical designing method for control system using a rough grasp of the unknown process property. We deal with a single-input single-output feedback control system with a fuzzy controller. The process property is roughly estimated by the step response, and the fuzzy controller is interactively modified according to the operator's requests. The modifying rules mainly derived from computer simulation are useful for almost every process, such as an unstable process and a non-minimum phase process. The fuzzy controller is tuned by taking notice of four characteristics of the step response: (1) rising time, (2) overshoot, (3) amplitude and (4) period of vibration. The tuning position of the controller is fourfold: (1) antecedent gain factor GE or GCE, (2) consequent gain factor GDU, (3) arrangement of the antecedent fuzzy labels and (4) arrangement of the control rules. The rules give an instance to the respective items of the controller in an effective order. The modified fuzzy PI controller realizes a good response of a stable process. However, because the GDU tuning becomes difficult for the unstable process, it is necessary to evaluate the stability of the process from the initial step response. The fuzzy PI controller is applied to the process whose initial step response converges with GDU tuning. The fuzzy PI controller with modified sampling time is applied to the process whose step response converges under the repeated application of the GDU tuning. The fuzzy PD controller is applied to the process whose step response never converges by the GDU tuning.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.31-40
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• 2003

Most face recognition systems are based on 2D images and applied in many applications. However, it is difficult to recognize a face when the pose varies severely. Therefore, head pose estimation is an inevitable procedure to improve recognition rate when a face is not frontal. In this paper, we propose a novel head pose estimation algorithm for 3D face recognition. Given the 3D range image of an unknown face as an input, we automatically extract facial feature points based on the face curvature. We propose an Error Compensated Singular Value Decomposition (EC-SVD) method based on the extracted facial feature points. We obtain the initial rotation angle based on the SVD method, and perform a refinement procedure to compensate for remained errors. The proposed algorithm is performed by exploiting the extracted facial features in the normaized 3D face space. In addition, we propose a 3D nearest neighbor classifier in order to select face candidates for 3D face recognition. From simulation results, we proved the efficiency and validity of the proposed algorithm.