• 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 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.

• Analytical Science and Technology
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• v.29 no.3
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• pp.142-153
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• 2016

In crime scene investigation, fingerprint identification is regarded to be one of the most important techniques for personal identification. However, objective and unbiased evaluation methods that would compare the fingerprints with diverse available and developing methods are currently lacking. To develop an objective and quantitative method to improve fingerprint evaluation, a preliminary study was performed to extract useful research information from the analysis with densitometric image analysis (CP Atlas 2.0) and the Automated Fingerprint Identification System (AFIS) for the developed fingerprints on porous surfaces. First, inked fingerprints obtained by varying pressure (kg.f) and pressing time (sec.) to find optimal conditions for obtaining fingerprint samples were analyzed, because they could provide fingerprints of a relatively uniform quality. The extracted number of minutiae from the analysis with AFIS was compared with the calculated areas of friction ridge peaks from the image analysis. Inked fingerprints with a pressing pressure of 1.0 kg.f for 5 seconds provided the most visually clear fingerprints, the highest number of minutiae points, and the largest average area of the peaks of the friction ridge. In addition, the images of the developed latent fingerprints on thermal paper with the iodine fuming method were analyzed. Fingerprinting condition of 1.0 kg.f/5 sec was also found to be optimal when generating highest minutiae number and the largest average area of peaks of ridges. Additionally, when the concentration of ninhydrin solution (0.5 % vs. 5 %) was used to compare the developed latent fingerprints on print paper, the best fingerprinting condition was 2.0 kg.f/5 sec and 5 % of ninhydrin concentration. It was confirmed that the larger the average area of the peaks generated by the image analysis, the higher the number of minutiae points was found. With additional tests for fingerprint evaluation using the densitometric image analysis, this method can prove to be a new quantitative and objective assessment method for fingerprint development.

• Journal of Plant Biotechnology
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• v.37 no.1
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• pp.12-24
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• 2010

Plant metabolomics is a research field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. Metabolomics or metabolite fingerprinting techniques usually involves collecting spectra of crude solvent extracts without purification and separation of pure compounds or not in standardized conditions. Therefore, that requires a high degree of reproducibility, which can be achieved by using a standardized method for sample preparation and data acquisition and analysis. In plant biology, metabolomics is applied for various research fields including rapid discrimination between plant species, cultivar and GM plants, metabolic evaluation of commercial food stocks and medicinal herbs, understanding various physiological, stress responses, and determination of gene functions. Recently, plant metabolomics is applied for characterization of gene function often in combination with transcriptomics by analyzing tagged mutants of the model plants of Arabidopsis and rice. The use of plant metabolomics combined by transcriptomics in functional genomics will be the challenge for the coming year. This review paper attempted to introduce current status and prospects of plant metabolomics research.

• Food Science of Animal Resources
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• v.22 no.4
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• pp.301-309
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• 2002

This study was carried out to develop the breed-specific DNA markers for breed identification of Korean native goat meat using amplified fragment length polymorphism (AFLP)-PCR techniques. The genomic DNAs of Korean native goat, imported black goat and four dairy goat breeds(Saanen, Alpine, Nubian and Toggenburg) were extracted from muscle tissues or blood. Genomic DNA was digested with a particular combination of two restriction enzymes with 4 base(Mse I and Taq I) and 6 base(EcoR I and Hind III) recognition sites, ligated to restriction specific adapters and amplified using the selective primer combinations. In AFLP profiles of polyacrylamide gels, the number of scorable bands produced per primer combination varied from 36 to 74, with an average of 55.5. A total of 555 bands were produced, 149(26.8%) bands of which were polymorphic. Among the ten primer combinations, two bands with 2.01 and 1.26 kb in M13/H13 primer and one band with 1.65 kb in E35/H14 primer were found to be breed-specific AFLP markers in Korean native goat when DNA bands were compared among the goat breeds. In the E35/H14 primer combination, 2.19, 2.03, 0.96 and 0.87 kb bands detected in imported black goat, 2.13 kb band in Saanen breed and 2.08 kb band in Nubian breed were observed as breed-specific bands showing differences between goat breeds, respectively. The E35/H14 primer combination produced four DNA bands distinguished between Korean native goat and Saanen breed. The is study suggested that the breed specific AFLP bands could be used as DNA markers for the identification of Korean native goat meat from imported black goat and dairy goat meats.

• Korean Security Journal
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• no.47
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• pp.7-36
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• 2016

The security providers industry, often referred to as an industry with unconfined growth ceiling, has entered a remarkable mass-growth phase since the 1980. In the modern era, private-sector security increasingly cover functions relating to general security awareness (including counter-terrorism) in partnership with State bodies, and the scale of operations continue to accelerate, relative to the expanding roles. In the era of pluralisation of policing, there has been widening efforts pursued to develop a range of regulatory strategies internationally in order to manage such growth and development. To date, in South Korea, a diverse set of industry review studies have been conducted. However, the analyses have been conventionally confined to North America, Britain, Germany and Japan, while developments in other world regions remain unassessed. This article is intended to inform the drivers and determinants of regulatory reforms in Australia, and examine the effectiveness of the main pillars of licensing innovations. Over the past decades, the Australian regime has undergone a wave of reforms in response to emerging issues, and in recognition of the industry as a 'public good' due to underpopulation density and the resulting security challenges. The focus of review in this study was on providing a detailed review of the regulatory approach taken by Australia that has expanded police-private security co-operation since the 1980s. The emphasis was on examining the core pillars of risk management strategies and oversight practices progressed to date and evaluating areas of possible improvement in regulation relative to South Korea. Overall, this study has identified three key features of Australian regime: (1) close checks on questionable close associates (including fingerprinting), (2) power of inspection and seizure without search warrant, (3) the 'three strikes' scheme. The rise of the private security presence in day-to-day policing operations means that industry warrant some intervening government-sponsored initiative. The overall lessons learnt from the Australian case was taken into account in determining the following checks and balances that would provide the ideal setting for the best-practice arrangement: (1) regulatory measure should be evaluated against a set of well-defined indicators, such as the merits of different enforcement tools for each given risk, (2) information about regulatory impacts should be analysed by a specialist research institute, (3) regulators should be innovative in applying a range of strategies available to them by employing a mixture of compliance promotional strategies, and adjust the mix as required.