• Korean Journal of Veterinary Research
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• v.47 no.1
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• pp.33-41
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• 2007

Streptococcus spp. comprising Streptococcus (S.) uberis S. dysgalactiae strains is major causeof bovine mastitis from particularly well-managed or low somatic cell count herds that have successfullycontrolled contagious pathogens. In this study, antimicrobial susceptibility and genetic characteristics of S.uberis isolated from clinical or subclinical mastitis milk at 2003 were investigated. Eighty seven isolatesof Streptococus spp. were identified by the conventional biochemical methods. The antimicrobialsusceptibility by disk diffusion method was determined for 46 S. uberis, 11 S. bovis, 10 S. oralis, 6 S.uberis and 14 other Streptococcus spp.. Overall, the tested strains were susceptible to tetracycline (11.5%),amikacin (14.9%), streptomycin (16.1%), neomycin (26.4%), kanamycin (35.6%), gentamicin (65.2%),oxacillin (70.1%), ampicillin (75.9%), chloramphenicol (78.2%), and cephalothin (97.7%). Additionally, S.uberis strains were susceptible to pencillin G (97.8%), but resistant to erythromycin (76.0%) by minimalinhibitory concentration test. The multiple-drug resistance rate of isolated bacteria to 4 more thanamplification fingerprinting patterns amplifed with primer 8.6d showed that 3 to 8 number of distinguishableDNA fragments ranged from 180 bp to 1,20 bp. Thirty seven isolates of S. uberis strains were subtypedinto 8 distinct patterns. Each subtype revealed a typical pattern of antimicrobial susceptibilities. Thesefindings demonstrate that S. uberis isolates were mastitis pathogens of diverse serotypes, and oftenencountered the diverse resistant patterns.

• Molecules and Cells
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• v.22 no.1
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• pp.119-125
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• 2006

The rat is an accepted model for studying human psychiatric/neurological disorders. We provide a protocol for total soluble protein extraction using trichloroacetic acid/acetone (TCA/A) from rat (female) whole brain, 10 brain regions and the pituitary gland, and show that two-dimensional gel electrophoresis (2-DGE) using precast immobilized pH (4-7) gradient (IPG) strip gels (13 cm) in the first dimension yields clean silver nitrate stained protein profiles. Though TCA/A precipitation may not be "ideal", the important choice here is the selection of an appropriate lysis buffer (LB) for solubilizing precipitated proteins. Our results reveal enrichment of protein spots by use of individual brain regions rather than whole brain, as well as the presence of differentially expressed spots in their proteomes. Thus individual brain regions provide improved protein coverage and are better suited for differential protein detection. Moreover, using a phosphoprotein-specific dye, ingel detection of phosphoproteins was demonstrated. Representative high-resolution silver nitrate stained proteome profiles of rat whole brain total soluble protein are presented. Shortcomings apart (failure to separate membrane proteins), gel-based proteomics remains a viable option, and 2-DGE is the method of choice for generating high-resolution proteome maps of rat brain and brain regions.

• Journal of the korean academy of Pediatric Dentistry
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• v.25 no.2
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• pp.292-303
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• 1998

The arbitrary primer polymerase chain reaction(AP-PCR) and Southern blot restriction fragment length polymorphism(RFLP) were used to genotype the cariogenic pathogen S. mutans in children. Following the morphologic chracteristics of colony on selective medium for S. mutans, total genomic DNA from 155 strains was extracted by conventional methods. Among 155 strains, 143 strains (92.3%) were confirmed S. mutans by PCR with dexA gene and 114 strains were used in this study. Three random sequence 10-base oligonucleotide primers were chosen for AP-PCR. The amplified DNA products were separated electrophoretically in a 2% agarose gel containing ethidium bromide and the banding patterns were compared among different strains. For RFLP analysis, DNA was digested with EcoRI and BamHI, separated on a 0.7 % agarose gel and transferred to a nylon membrane. The membrane was probed with a previously characterised 1.6 kilobases (kb) DNA fragment cloned from gtf B gene of S. mutans. The probe was labeled with isotope[$^{32}P-{\alpha}CTP$], and hybridized fragments were detected with intensifying screen. AP-PCR produced 4-8 DNA bands in the 0.25-10 kb regions and distinguished 9, 10 or 12 genotypes, depending on the specific primer used. Southern blot RFLP analysis revealed 2 hybridization patterns consisting of 1 DNA fragments 450, 500 bp. These results indicate that AP-PCR is more discriminative method for genotyping of S. mutans.

• Food Science of Animal Resources
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• v.33 no.2
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• pp.281-286
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• 2013

Salmonella Gallinarum (SG) is known as an important pathogen that causes fowl typhoid in chickens. To investigate SG outer-membrane proteins (OMPs) as a vaccine candidate, we used proteomic mapping and database analysis techniques with extracted OMPs. Also, extracted OMPs were evaluated in several aspects to their safety, immune response in their host and protective effects. Our research has established a proteomic map and database of immunogenic SG-OMPs used as inactive vaccine against salmonellosis in chickens. A total of 22 spots were detected by 2-dimensional gel electrophoresis and immunogenic protein analysis. Eight spots were identified by Matrix-Assisted Laser Desorption/Ionization-Time of Flight-Mass spectrometry (MALDI-TOF-MS) and peptide mass fingerprinting (PMF) and categorized into four different types of proteins. Among these proteins, OmpA is considered to be an immunogenic protein and involved in the hosts' immune system. To estimate the minimum safety dose in chickens, 35 brown layers were immunized with various concentrations of OMPs, respectively. Consequently, all chickens immunized with more than a $50{\mu}g$ dose were protected against challenges. Moreover, intramuscular administration of OMPs to chickens was more effective compared to subcutaneous administration. These results suggest that the adjuvanted SG-OMP vaccine not only induces both the humoral and cellular immune response in the host but also highly protects the hosts' exposed to virulent SG with $50{\mu}g$ OMPs extracted by our method.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.25-30
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• 2019

Magnetic sensors have the disadvantage that their vector values differ depending on the direction. In this paper, we propose a magnetic vector calibration method for geomagnetic-based indoor localization estimates. The fingerprinting technique used in geomagnetic-based indoor localization the position by matching the magnetic field map and the magnetic sensor value. However, since the moving direction of the current user may be different from the moving direction of the person who creates the magnetic field map at the collection time, the sampled magnetic vector may have different values from the vector values recorded in the field map. This may substantially lower the positioning accuracy. To avoid this problem, the existing studies use only the magnitude of magnetic vector, but this reduces the uniqueness of the fingerprint, which may also degrade the positioning accuracy. In this paper we propose a vector calibration algorithm which can adjust the sampled magnetic vector values to the vector direction of the magnetic field map by using the parametric equation of a circle. This can minimize the inaccuracy caused by the direction mismatch.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.898-903
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• 2020

In this paper, we propose an indoor logistic tracking system that identifies the location and inventory of the logistics in the room based on fingerprints. Through this, we constructed the actual infrastructure of the logistics center and designed and implemented the logistics management system. The proposed system collects the signal strength through the location terminal and generates the signal map to locate the goods. The location terminal is composed of a UHF RFID reader and a wireless LAN card, reads the peripheral RFID signal and the signal of the wireless AP, and transmits it to the web server. The web server processes the signal received from the location terminal and stores it in the database, and the user uses the data to produce the signal map. The proposed system combines UHF RFID with existing fingerprinting method to improve performance in the environment of querying multiple objects.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.75-87
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• 2009

This paper, which is about the method of creating the audio fingerprint and comparing with the audio data, presents how to distinguish music using the characteristics of audio data. It is a process of applying the Difference of Gaussian (DoG: generally used for recognizing images) to the audio data, and to extract the music that changes radically, and to define the location of fingerprint. This fingerprint is made insensitive to the changes of sound, and is possible to extract the same location of original fingerprint with just a portion of music data. By reducing the data and calculation of fingerprint, this system indicates more efficiency than the pre-system which uses pre-frequency domain. Adopting this, it is possible to indicate the copyrighted music distributed in internet, or meta information of music to users.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.55-58
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• 2024

In this paper, we propose a design and implementation of big data-based fine dust anomaly detection machine learning system. The proposed is system that classifies the fine dust air quality index through meteorological information composed of fine dust and big data. This system classifies fine dust through the design of an anomaly detection algorithm according to the outliers for each air quality index classification categories based on machine learning. Depth data of the image collected from the camera collects images according to the level of fine dust, and then creates a fine dust visibility mask. And, with a learning-based fingerprinting technique through a mono depth estimation algorithm, the fine dust level is derived by inferring the visibility distance of fine dust collected from the monoscope camera. For experimentation and analysis of this method, after creating learning data by matching the fine dust level data and CCTV image data by region and time, a model is created and tested in a real environment.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.