• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.426-433
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• 2008

In this paper, we present a method to improve the performance of the four transmit antenna quasi-orthogonal space-time block code (STBC) in the coded system. For the four transmit antenna case, the quasi-orthogonal STBC consists of two symbol groups which are orthogonal to each other, but intra group symbols are not. In uncoded system with the matched filter detection, constellation rotation can improve the performance. However, in coded systems, its gain is absorbed by the coding gain especially for lower rate code. We propose an iterative decoding method to improve the performance of quasi-orthogonal codes in coded systems. With conventional quasi-orthogonal STBC detection, the joint ML detection can be improved by iterative processing between the demapper and the decoder. Simulation results shows that the performance improvement is about 2dB at 1% frame error rate.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2455-2458
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• 2003

In this paper, the Classification of Energy Labeling has been Proposed. Energy Parameters of input signal which is extracted from each phoneme is labelled. And groups of labelling according to detected energies of input signals are detected. Next, DTW processes in a selected group of labeling. This leads to DTW processing faster than a previous algorithm. In this Method, because an accurate detection of parameters is necessary on the assumption in steps of a detection of speeching duration and a detection of energy parameters, variable windows which are decided by pitch period is used. Extract algorithms don't search for exact frame energy, because 256 frame window-sizes is fixed. For this reason, a new energy extraction method has been proposed. A pitch period is detected firstly; next window scale is decided between 200 frames and 300 frames. The proposed method make it possible to cancel an influence of windows.

• Journal of Food Hygiene and Safety
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• v.12 no.1
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• pp.71-77
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• 1997

Sulfonamides, a therapeutically important group of antimicrobial drugs, are widely used to treat and prevent the acute systemic and skin infections in dairy cattle. They also pose an economic hazard through inhibition of growth of dairy starter cultures. This study was carried out to compare four screening methods for detection of sulfamethazine in milk and determine the positive milk sample by HPLC method. Sulfamethazine was used to spike at five levels of sulfamethazine. The Lac-Tek test and CharmII test were also consistent better than TTCII test and Delvo SP test in sulfamethazine detection. Analysis probabilities of obtaining a positive response with TTCII test and Delvo SP test assay at 50 ppb sulfamethazine level in milk samples were only 14%, 42% each. Whereas using the Lac-Tek test and CharmII test would have resulted in 100% identification of the five levels. Determination of sufamethazine using the HPLC method in the spiked milk were 10.64, 19.30, 30.76,38.83 and 50.23 ppb, respectively.

• Bulletin of the Korean Chemical Society
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• v.23 no.4
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• pp.599-603
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• 2002

A selective enzyme-linked immunosorbent assay (ELISA) for the insecticide isofenphos was developed. Three different analogues (haptens) of isofenphos were synthesized and were coupled to carrier proteins through the pesticide thiophosphate group t o use as immunogens or coating antigens. Rabbits were immunized with one of the haptens coupled to BSA for production of polyclonal antibodies and the sera were screened against each of the other two haptens coupled to ovalbumin (OVA). Using the sera of highest specificity, an antigen-coated ELISA was developed, which showed an I50 of 96 ng/mL with the detection limit of 2 ng/mL. The antibodies showed negligible cross-reactivity with other organophosphorus pesticides and the phenol metabolite of isofenphos, which makes the developed assay suitable for the selective detection of isofenphos. An antibody-coated ELISA was also developed, which showed an I50 of 580 ng/mL with a detection limit of 70 ng/mL.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.960-966
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• 2011

In this paper, an $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ fault detection and isolation (FDI) observer design problem is investigated for discrete-time delayed systems. To that end, a bank consisting of the sensor's number of observers is introduced. Each residual should be sensitive to a certain partial group of faults, but robust against the disturbance as far as possible. We formulate this multiobjective FDI problem as $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ observers design problem. Sufficient design condition is expressed as iterative linear matrix inequalities. The fault is then detected and isolated by evaluating the residuals through an FDI decision logic. A computer simulation is provided for verification of the proposed technique.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.757-759
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• 2003

Understanding the area of the rice paddy fields is important, and suitable for it the remote sensing. SAR is effective to the monitor in Southeast Asia with the rainy season. The detection of the filled rice paddy fields by RADARSAT was tried in the north part of Bangkok Thailand, and in the Mekong river valley Cambodia, which ware the main rice production country in Southeast Asia. We get observation data by RADARSAT and fields all through a year around Bangkok. However, because the flood had occurred on the study area in 2002 observed, the detection only of the rice fields ware difficult.

• Applied Science and Convergence Technology
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• v.25 no.3
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• pp.61-65
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• 2016

Here, the rapid detection of Salmonella typhimurium by a portable surface plasmon resonance (SPR) biosensor in which the beam from a diode laser is modulated by a rotating mirror is reported. Using this system, immunoassay based on lipopolysaccharides (LPS)-specific monoclonal anti-Salmonella antibody was performed. For the purpose of orientation-controlled immobilization of antibodies on the SPR chip surface, the cysteine-mediated immobilization method, which is based on interaction between a gold surface and a thiol group (-SH) of cysteine, was adopted. As a result, using the portable SPR-based immunoassay, we detected S. typhimurium in the range from 10^7 CFU/mL to 10^9 CFU/mL within 1 hour. The results indicate that the portable SPR system could be potentially applied for general laboratory detection as well as on-site monitoring of foodborne, clinical, and environmental agents of interest.

• Journal of Veterinary Clinics
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• v.24 no.2
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• pp.169-171
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• 2007

The aim of this study was to detect bovine viral diarrhea virus (BVDV) from calves in Chonbuk province. Blood samples were taken from ninety-two dairy calves. Capture enzyme-linked immunosorbent assay (ELISA) was used to detect BVDV. BVDV were detected in eight out of ninety-two (8.6%) dairy calves. BVDV were detected in one of twenty five of female calves and one of twenty three of male calves of 4 months old, whereas in the 5 months age group, BVDV were detected in low of twenty three of female calves and two of twenty one of male calves. There were no significant differences (p>0.05) in the detection rate of BVDV on the basis of sex. On the other hand, ages of calves had significant differences (p<0.05) on the prevalence of BVDV.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.267-277
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• 2020

It is important to understand the exact habitat distribution of endangered species because of their decreasing numbers. In this study, we build a system with a deep learning module that collects the image data of endangered animals, processes the data, and saves the data automatically. The system provides a more efficient way than human effort for classifying images and addresses two problems faced in previous studies. First, specious answers were suggested in those studies because the probability distributions of answer candidates were calculated even if the actual answer did not exist within the group. Second, when there were more than two entities in an image, only a single entity was focused on. We applied an object detection algorithm (YOLO) to resolve these problems. Our system has an average precision of 86.79%, a mean recall rate of 93.23%, and a processing speed of 13 frames per second.