• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.139-147
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• 2009

This paper proposed the context awareness reasoning system to provide the personalized services dynamically in a ubiquitous mobile environments. The proposed system is designed to provide the personalized services to mobile users and consists of the context aggregator and the knowledge manager. The context aggregator can collect information from networks through Open API Gateway as well as sensors in a various ubiquitous environment. And it can also extract the place types through the geocoding and the social address domain ontology. The knowledge manager is the core component to provide the personalized services, and consists of activity reasoner, user pattern learner and service recommender to provide the services predict by extracting the optimized service from user situations. Activity reasoner uses the ontology reasoning and user pattern learner learns with previous service usage history and contexts. And to design service recommender easy to flexibly apply in dynamic environments, service recommender recommends service in the only use of current accessible contexts. Finally, we evaluate the learner and recommender of proposed system by simulation.

• The Journal of Korean Association of Computer Education
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• v.9 no.2
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• pp.101-109
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• 2006

We propose an adaptive digital watermarking algorithm using HVS(human visual system) and SOM(Self-Organizing Map) among neural networks. This method adjusts adaptively the strength of the watermark which is embedded in different blocks according to block classification in DCT(Discrete Cosine Transform) domain. All blocks in 3 classes out of 4 are selected to embed a watermark. Watermark sequences are embedded in 6 lowest frequency coefficients of each block except the DC component. The experimental results are excellent.

• Journal of the Optical Society of Korea
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• v.20 no.5
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• pp.601-606
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• 2016

In this study, in order to analyze the low-temperature sintering process of silver and copper nanoparticles, we calculate their melting temperatures and surface melting temperatures with respect to particle size. For this calculation, we introduce the concept of mean-squared displacement of the atom proposed by Shi (1994). Using a parameter defined by the vibrational component of melting entropy, we readily obtained the surface and bulk melting temperatures of copper and silver nanoparticles. We also calculated the absorption cross-section of nanoparticles for variation in the wavelength of light. By using the calculated absorption cross-section of the nanoparticles at the melting temperature, we obtained the laser threshold energy for the sintering process with respect to particle size and wavelength of laser. We found that the absorption cross-section of silver nanoparticles has a resonant peak at a wavelength of close to 350 nm, yielding the lowest threshold energy. We calculated the intensity distribution around the nanoparticles using the finite-difference time-domain method and confirmed the resonant excitation of silver nanoparticles near the wavelength of the resonant peak.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1451-1456
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• 2013

This paper propose a method for fast convergence technique in frequency domain independent component analysis (FDICA) using eigenanalysis. It important, such as SONAR system, to eliminate the interference sources through fast algorithm. Through eigenanalysing a two-by-two delayed mixture case, information of delay can be used for initial weighting parameters. Simulations show the improved performances in convergence speed and noise rejection rate. The proposed method can present close weights for optimal convergence, noise can be diminished drastically about 3 times epoch, and get the better resultss with 1~3dB than the conventional method.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.27-39
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• 2005

The Semantic Web has increased the interest in ontologies recently Ontology is an essential component of the semantic web and continues to change and evolve. We consider versions management schemes in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. Our change specification is represented by a set of changes. A set of changes consists of instance data change, structural change, and identifier change. In order to support a query in ontology versions, we consider temporal dimension includes valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the ontology versions management schemes that are 1) storing all the change sets, 2) storing the aggregation of change sets periodically, and 3) storing the aggregation of change sets using an adaptive criterion. We conduct a set of experiments to compare the performance of each versions management schemes. We present the experimental results for evaluating the performance of the three version management schemes from scheme 1 to scheme 3. Scheme 1 has the least storage usage. The average response time in Scheme 1 is extremely large, those of Scheme 3 is smaller than Scheme 2. Scheme 3 shows a good performance relatively.

• Microbiology and Biotechnology Letters
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• v.38 no.2
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• pp.117-123
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• 2010

BT toxin is produced by a soil bacterium Bacillus thuringiensis and has long been used as a biological insecticide without any competition. Recently, Photorhabdus, a symbiotic bacterium from entomopathogenic nematodes, family Heterorhabditae, has been researched and discussed as alternatives to B. thuringiensis. Photorhabdus, which lives in the gut of entomopathogenic nematodes, is a highly virulent pathogen of a wide range of insect larvae. When an insect is infected by the nematodes, the bacteria are released into the cadaver, and produce a number of insecticidal toxins. The biological role of the different Photorhabdus toxins in the infection process is still unclear. Photorhabdus toxin complex (Tc) is highly secreted gut-active toxin and has been characterized as a potent three-component (A, B and C) insecticidal protein complex. These components are necessary for full oral activity against insect larvae. The Photorhabdus PirAB binary toxins exhibit a potent injectable activity for Galleria mellonella larvae, and have oral toxicity against mosquitoes and caterpillar pest Plutella xylostella. Other toxin, 'makes caterpillars floppy' (Mcf) showed injectable activity on caterpillars. Recombinant Mcf triggers apoptosis in both insect hemocytes and the midgut epithelium and carries a BH3 domain. In this review, the relationship between the Photorhabdus and the nematode is discussed and recent important insecticidal toxins from Photorhabdus are described.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.145-150
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• 1993

It is an important component of the diagnosis to research the morphological changes of EMG in pathological conditions. In order to provide an EMG signal resulting from a predetermined neuromuscular pathophysiology, we have initially developed a mathmatical model of electromyographic interference pattern(IP). It can be used to study the variation of the IP resulting from morphological and electrophysiological changes occurring in disease states, because the model computes the IP from the underlying fiber and muscle structure. We performed quantative analysis or the model output, focusing on IPs resulting from simulations of dystrophic fiber loss and the MU denervation and reinnervation typical of neuropathies. To discribe the characteristics of IPs associated with these pathologies, a set of frequency domain discriptors, activity, mobility, and complexity were used, as well as several measures of the spectral density function. These discriptors demonstrate distinct patterns of variation corresponding to morphological changes observed in disease states, and closely with results obtained from the classical method, turn/amp technique.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.102-106
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• 2008

Forensic Marking is the technology that enables the service providers (SP) to identify the illegal digital contents distributors by first inserting markings (data indicating the user information and playback time) in realtime into the digital contents at time of playback of digital contents, and then later by extracting inserted markings from the contents which are illegally captured from the multimedia device such as IPTV STBs and distributed over the Internet. Digital Rights Management (DRM), which is a very popular content protection technology, has the security hole that can be vulnerable because the encrypted digital contents are transformed into their original plaintext forms after the decrypting process on the STBs. Therefore Forensic Marking (FM) has now become a companion content protection solution to DRM. This article describes a new way of tracking up to 4 illegal content users in FM implementation using the blue-difference chroma component of YCbCr color space. This FM technology has many advantages like fast processing time and easy portability to STB devices compared to that of the traditional watermarking processing in the frequency domain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.565-568
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• 2006

In the luminance and chrominance signal, luminance signal creates gray images, and is capable of making each color component compatible with monochrome system. And color components of luminance and chrominance signals are useful to encode or convert the signal because they have low correlation. Each color signal has low correlation statistically, but they are not independent of one another. Therefore, this paper proposes the watermark inserting algorithm for luminance and chrominance signal in the domain of frequency founded on wavelet, considering the interdependent characteristics of color components. Therefore, it can guarantee the robustness and invisible of digital watermark.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.714-720
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• 2016

Rubbing and misalignment are the most usual faults that occurs in rotating machinery and with them severe effect on power plant availability. Especially blade rubbing is hard to detect on FFT spectrum using the vibration signal. In this paper, the possibility of feature analysis of vibration signal is confirmed under blade rubbing and misalignment condition. And the lab-scale rotor test device provides the blade rubbing and shaft misalignment modes. Feature selection based on GA (genetic algorithm) is processed by the extracted feature of the time domain. Then, classification of the features is analyzed by using SVM (support vector machine) which is one of the machine learning algorithm. The results of features selection based on GA compared with those based on PCA (principal component analysis). According to the results, the possibility of feature analysis is confirmed. Therefore, blade rubbing and shaft misalignment can be diagnosed by feature of vibration signal.