• Journal of IKEEE
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• v.15 no.2
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• pp.179-189
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• 2011

This paper presents an SVC based multi-channel transmission technique. Transmission of high definition multimedia and its service efficiency can be significantly improved by the proposed method. In this method, the HD stream is divided into the two layer streams, i.e., a base layer stream and an enhancement layer stream. The divided streams are transmitted through a primary channel and an auxiliary channel, respectively. The proposed technique provides a noble mode switching technique which enables a seamless service of HD multimedia even under the conditions of abrupt and intermittent deterioration of the auxiliary channel. When the enhancement layer stream is disrupted by the channel monitoring in the mode switching algorithm, the algorithm works further to maintain the spatial and time resolution of the HD multimedia by upsampling and interpolating the base layer stream, consequently serving for the non disrupted play of the media. Moreover, the adoption of an adaptive switching algorithm significantly reduces the frequency of channel disruption avoiding the unnecessary switching for the short period variations of the channel. The feasibility of the proposed technique is verified through the simulation study with an example application to the simultaneous utilization of both Ku and Ka bands for HD multimedia broadcasting service. The rainfall modeling and the analysis of the satellite channel attenuation characteristics are performed to simulate the quality of service performance of the proposed HD broadcasting method. The simulation results obtained under a relatively poor channel (weather) situations show that the average lasting period of enhancement layer service is extended from 9.48[min] to 23.12[min] and the average switching frequency is reduced from 3.84[times/hour] to 1.68[times/hour]. It is verified in the satellite example that the proposed SVC based transmission technique best utilizes the Ka band channel for the service of HD broadcasting, although it is characterized by its inherent weather related poor reliability causing severe limitations in its independent application.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.31-43
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• 2000

This paper presents a novel algorithm lot extraction of the eye and mouth fields (facial features) from 2D gray level face images. First of all, it has been found that Eigenfeatures, derived from the eigenvalues and the eigenvectors of the binary edge data set constructed from the eye and mouth fields are very good features to locate these fields. The Eigenfeatures, extracted from the positive and negative training samples for the facial features, ate used to train a MultiLayer Perceptron(MLP) whose output indicates the degree to which a particular image window contains the eye or the mouth within itself. Second, to ensure robustness, the ensemble network consisting of multiple MLPs is used instead of a single MLP. The output of the ensemble network becomes the average of the multiple locations of the field each found by the constituent MLPs. Finally, in order to reduce the computation time, we extracted the coarse search region lot eyes and mouth by using prior information on face images. The advantages of the proposed approach includes that only a small number of frontal faces are sufficient to train the nets and furthermore, lends themselves to good generalization to non-frontal poses and even to other people's faces. It was also experimentally verified that the proposed algorithm is robust against slight variations of facial size and pose due to the generalization characteristics of neural networks.

• Journal of Life Science
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• v.30 no.9
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• pp.813-818
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• 2020

The archaeal clusters of orthologous genes (arCOG) algorithm, which identifies common genes among archaebacterial genomes, was used to identify conservative genes among 168 archaebacterial strains. The numbers of conserved orthologs were 14, 10, 9, and 8 arCOGs in 168, 167, 166, and 165 strains, respectively. Among 41 conserved arCOGs, 13 were related to function J (translation, ribosomal structure, and biogenesis), and 10 were related to function L (replication, recombination, and repair). Among the 14 conserved arCOGs in all 168 strains, 6 arCOGs of tRNA synthetase comprised the highest proportion. Of the remaining 8 arCOGs, 2 are involved in reactions with ribosomes, 2 for tRNA synthesis, 2 for DNA replication, and 2 for transcription. These results showed the importance of protein expression in archaea. For the classes or orders having 3 or more members, genomic analysis was performed by averaging the distance values of the conservative arCOGs. Classes Archaeoglobi and Thermoplasmata of the phylum Euryarchaeota showed the lowest and the highest average of distance value, respectively. This study can provides data necessary for basic scientific research and the development of antibacterial agents and tumor control.

• Economic and Environmental Geology
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• v.45 no.5
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• pp.503-512
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• 2012

We performed DInSAR (Differential Interferometric SAR) and SBAS (Small BAseline Subset) analysis using spaceborne SAR (Synthetic Aperture Radar) in order to detect a surface subsidence in Taebaek area, Kangwon, which are suitable to the monitoring of broad and inaccessible areas. During the period from October 2006 to June 2010, we acquired twenty-three ALOS PALSAR data sets (path/frame=425/730) for this study. The ninety-six differential interferograms with a perpendicular baseline less than 1100 m were constructed by ROI_PAC, then the mean velocity map of surface displacement was derived from SBAS analysis. As a result, it was confirmed that the ground displacement occurred about 4 cm/yr at Seokgong-Jangseong and Kyungdong mines and 2 cm/yr at Saehan-Eoryong-Jungdong and Hwangji mines in Taebaek area, Kangwon. It seems that the subsidence in study area is closely related to mining activities because the most of subsiding areas are well matched with mining areas. The subsidence at Kyungdong mine shows continuous and fast velocity in about $2{\times}2$ km area. Therefore the further analysis and the effort to prevent disaster are required in this area.

• Journal of Life Science
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• v.25 no.9
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• pp.1007-1013
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• 2015

A COG (Cluster of Orthologous Groups of proteins) algorithm was applied to detect conserved genes in 711 prokaryotes. Only COG0080 (ribosomal protein L11) was common among all the 711 prokaryotes analyzed and 58 COGs were common in more than 700 prokaryotes. Nine COGs among 58, including COG0197 (endonuclease III) and COG0088 (ribosomal protein L4), were conserved in a form of one gene per one organism. COG0008 represented 1356 genes in 709 of the prokaryotes and this was the highest number of genes among 58 COGs. Twenty-two COGs were conserved in more than 708 prokaryotes. Of these, two were transcription related, four were tRNA synthetases, eight were large ribosomal subunits, seven were small ribosomal subunits, and one was translation elongation factor. Among 58 conserved COGs in more than 700 prokaryotes, 50 (86.2%) were translation related, and four (6.9%) were transcription related, pointing to the importance of protein-synthesis in prokaryotes. Among these 58 COGs, the most conserved COG was COG0060 (isoleucyl tRNA synthetase), and the least conserved was COG0143 (methionyl tRNA synthetase). Archaea and eubacteria were discriminated in the genomic analysis by the average distance and variation in distance of common COGs. The identification of these conserved genes could be useful in basic and applied research, such as antibiotic development and cancer therapeutics.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.755-767
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• 2014

In this study, detailed air flow characteristics in an urban areas were analyzed using GIS data and a Computational Fluid Dynamics (CFD) model. For this, a building construction algorithm optimized for Geographic Information System (GIS) data with a vector format (Los Angeles region imagery acquisition consortium 2 geographic information system, LARIAC2 GIS) was used. In the LARIAC2 GIS data, building vertices were expressed as latitude and longitude. Using the model buildings constructed by the algorithm as the surface boundary data in the CFD model, we performed numerical simulations for two building-congested areas in Los Angeles using inflow information provided by California Air Resources Board. Comparing with the inflow, there was a marked difference in wind speed and direction within the target areas, which was mainly caused by the secondarily induced local circulations such as street-canyon vortices, horse-shoe vortices, and recirculation zones. In street canyons parallel to the inflow direction, wind speed increased due to a channeling effect and, in street canyons perpendicular to the inflow direction, vertically well developed vortices were induced. In front of a building, a horse-shoe vortex was developed near the surface and, behind a building, a recirculation zone was developed. Near the surface in the areas where the secondarily induced local circulations, wind speed remarkably increased. Overall, wind direction little (largely) changed at the areas where wind speed largely increased (decreased).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.678-686
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• 2019

In this study, marine heat waves on coastal waters of Republic of Korea were detected using satellite-based Sea Surface Temperature Anomaly (SSTA). The detected results were compared with the warm water issues reported by the National Institute of Fisheries Science (NIFS). Marine heat waves detection algorithm using SSTA based on a threshold has proposed. The threshold value was defined as 2℃ for caution and 3℃ for warning issues, respectively. Daily averaged SST data from July to September of 2017-2018 were used to generate SSTA. The satellite-based detection results were classified into nine areas according to the place names used in the NIFS warm water issues. In the comparison of frequency of marine heat waves occurrence to each area with the warm water issue, most areas in the southern coast showed a similar pattern, that is probably NIFS uses spatially well distributed buoys. On the other hand, other sea areas had about two times more satellite detection results. This result seems to be because NIFS only considers the water temperature data measured at limited points. The results of this study are expected to contribute to the development of a satellite-based warm/cold water monitoring system in coastal waters.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.273-283
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• 2020

Quantitative forecasting of groundwater levels for the assessment of groundwater variation and vulnerability is very important. To achieve this purpose, various time series analysis and machine learning techniques have been used. In this study, we developed a prediction model based on LSTM (Long short term memory), one of the artificial neural network (ANN) algorithms, for predicting the daily groundwater level of 11 groundwater wells in Hankyung-myeon, Jeju Island. In general, the groundwater level in Jeju Island is highly autocorrelated with tides and reflected the effects of precipitation. In order to construct an input and output variables based on the characteristics of addressing data, the precipitation data of the corresponding period was added to the groundwater level data. The LSTM neural network was trained using the initial 365-day data showing the four seasons and the remaining data were used for verification to evaluate the fitness of the predictive model. The model was developed using Keras, a Python-based deep learning framework, and the NVIDIA CUDA architecture was implemented to enhance the learning speed. As a result of learning and verifying the groundwater level variation using the LSTM neural network, the coefficient of determination (R²) was 0.98 on average, indicating that the predictive model developed was very accurate.