• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.268-273
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• 2006

차세대 무선 네트워크 (4G)는 새로운 무선 접속 기술의 개발과 함께 많은 연구가 필요한 분야이다. 그 중에서 특히 단말의 끊김없는 이동성을 제공해 주기 위한 핸드오버 기술이 가장 중요하다고 할 수 있다. 차세대 무선 네트워크는 새로운 무선 접속 기술과 함께 기존의 무선랜이나 이동통신망 등과 같이 사용될 것으로 예상되며, 네트워크 계층에서의 이동성 지원을 위하여 Mobile IPv6를 사용할 것으로 예상되는 네트워크이다. 이러한 네트워크에서 끊김없는 이동성을 제공해 주기 위해서는 현재까지 연구된 핸드오버 기능 및 구조에 대한 연구와 함께 보다 다양해진 네트워크 환경과 QoS 등을 고려한 종합적인 핸드오버 기능에 대한 연구가 필요하다. 본 논문에서는 차세대 무선 네트워크에서 단말의 끊김없는 핸드오버를 제공해 주기 위하여 필요한 기능들을 도출하고, 이들간의 유기적인 연관관계를 정의하여 다양한 네트워크 환경과 사용자의 우선순위, 어플리케이션의 QoS 요구 조건 등을 고려한 종합적인 핸드오버 기능 구조를 제안하고자 한다. 제안하는 핸드오버 구조는 Monitoring, Triggering, Handover의 세 가지 module로 나뉘어져 있으며, 각각은 필요에 따라 sub-module로 다시 세분화된다. 제안하는 핸드오버 구조의 가장 큰 특징은 핸드오버를 유발시킬 수 있는 여러 가지 요소를 종합적으로 고려하며 이들간의 수평적인 비교가 아닌 다단계 비교를 수행하여 보다 정확한 triggering이 가능하도록 한다. 또한 단말의 QoS 요구 사항을 보장하고 네트워크의 혼잡도(congestion) 및 부하 조절 (load balancing)을 위한 기능을 핸드오버 기능에 추가하여 효율적인 네트워크의 자원 사용이 가능하도록 설계하였다.서버로 분산처리하게 함으로써 성능에 대한 신뢰성을 향상 시킬 수 있는 Load Balancing System을 제안한다.할 때 가장 효과적인 라우팅 프로토콜이라고 할 수 있다.iRNA 상의 의존관계를 분석할 수 있었다.수안보 등 지역에서 나타난다 이러한 이상대 주변에는 대개 온천이 발달되어 있었거나 새로 개발되어 있는 곳이다. 온천에 이용하고 있는 시추공의 자료는 배제하였으나 온천이응으로 직접적으로 영향을 받지 않은 시추공의 자료는 사용하였다 이러한 온천 주변 지역이라 하더라도 실제는 온천의 pumping 으로 인한 대류현상으로 주변 일대의 온도를 올려놓았기 때문에 비교적 높은 지열류량 값을 보인다. 한편 한반도 남동부 일대는 이번 추가된 자료에 의해 새로운 지열류량 분포 변화가 나타났다 강원 북부 오색온천지역 부근에서 높은 지열류량 분포를 보이며 또한 우리나라 대단층 중의 하나인 양산단층과 같은 방향으로 발달한 밀양단층, 모량단층, 동래단층 등 주변부로 NNE-SSW 방향의 지열류량 이상대가 발달한다. 이것으로 볼 때 지열류량은 지질구조와 무관하지 않음을 파악할 수 있다. 특히 이러한 단층대 주변은 지열수의 순환이 깊은 심도까지 가능하므로 이러한 대류현상으로 지표부근까지 높은 지온 전달이 되어 나타나는 것으로 판단된다.의 안정된 방사성표지효율을 보였다. $^{99m}Tc$-transferrin을 이용한 감염영상을 성공적으로 얻을 수 있었으며, $^{67}Ga$-citrate 영상과 비교하여 더 빠른 시간 안에 우수한 영상을 얻을 수 있었다. 그러므로 $^{99m}Tc$-transierrin이 감염 병소의 영상진단에 사용될 수 있을 것으로 기대된다.리를 정량화 하였다. 특히 선

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.241-263
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• 2010

KoFlux is a Korean network of micrometeorological tower sites that use eddy covariance methods to monitor the cycles of energy, water, and carbon dioxide between the atmosphere and the key terrestrial ecosystems in Korea. KoFlux embraces the mission of AsiaFlux, i.e. to bring Asia's key ecosystems under observation to ensure quality and sustainability of life on earth. The main purposes of KoFlux are to provide (1) an infrastructure to monitor, compile, archive and distribute data for the science community and (2) a forum and short courses for the application and distribution of knowledge and data between scientists including practitioners. The KoFlux community pursues the vision of AsiaFlux, i.e., "thinking community, learning frontiers" by creating information and knowledge of ecosystem science on carbon, water and energy exchanges in key terrestrial ecosystems in Asia, by promoting multidisciplinary cooperations and integration of scientific researches and practices, and by providing the local communities with sustainable ecosystem services. Currently, KoFlux has seven sites in key terrestrial ecosystems (i.e., five sites in Korea and two sites in the Arctic and Antarctic). KoFlux has systemized a standardized data processing based on scrutiny of the data observed from these ecosystems and synthesized the processed data for constructing database for further uses with open access. Through publications, workshops, and training courses on a regular basis, KoFlux has provided an agora for building networks, exchanging information among flux measurement and modelling experts, and educating scientists in flux measurement and data analysis. Despite such persistent initiatives, the collaborative networking is still limited within the KoFlux community. In order to break the walls between different disciplines and boost up partnership and ownership of the network, KoFlux will be housed in the National Center for Agro-Meteorology (NCAM) at Seoul National University in 2011 and provide several core services of NCAM. Such concerted efforts will facilitate the augmentation of the current monitoring network, the education of the next-generation scientists, and the provision of sustainable ecosystem services to our society.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.47-59
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• 2017

Korean Economy has been developed by the Korean Government's Support for the Large-sized Firms. This Government Policy causes the Polarization between Large-sized and Micro-sized Firms Aggravated. Micro-sized Firms are distributed over the Whole Industry Area, and can also cause the Economic Crisis If They are crashed down. Therefore Government Policy for the Micro-sized Manufacturing Industry is very Important Issue. This Paper Focused on the Analysis of Current Status for the Shoes Micro Manufacturing Industry. For the Effective Analysis, This Paper uses the Statistical Data Open to the Public and also conducts the Survey for the Micro-sized Firms in Busan. Statistical Program is used for Analyzing the Collected Data and the Major Findings are as Follows. First, Shoes Industry is led by the Micro and Small & Medium sized Firms rather than the Large-sized. And the Micro-sized Firms are getting the High Rate among the Whole Shoes Industry. Busan is heavily populated Area as the Origin of Shoes Industry. Second, even though Most of the Owner of the Micro-sized Firms have the High Technology Skill Level, Worker's Aging Phenomenon gets Worse and causes the Technology Handing down to the Next Generation Difficult. Third, Because the Factory Facility of the Micro-sized Firms is Dirt and Unstable, the Modernized Manufacturing Infrastructure such as the Apartment Factory Facility is Necessary. Forth, as the Micro-sized Firms which have the Intangible Asset such as Patent is Few, the Government Policy for Encouraging the Patent Application is strongly Needed. Fifth, Entrepreneurship and Collaboration Mind between Micro-sized Firms are Lacked, so Establishment of the Cooperative Union is required. Finally, the Effort for the Systemic Planning for the Management is lacked, and the Introduction of the Management Innovation is strongly needed. The Limitation and Future Research Direction is also discussed.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.225-233
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• 2012

The 3D stereoscopic image contents have been emerging as the blue chip of the contents market of the next generation since the . However, all the 3D contents created commercially in the country have failed to enter box office. It is because the quality of Korean 3D contents is much lower than that of overseas contents and also current 3D post production process is based on 2D. Considering all these facts, the 3D editing process has connection with the quality of contents. The current 3D editing processes of the production case of are using the way that edits with the system on basis of 2D, followed by checking with 3D display system and modifying, if there are any problems. In order to improve those conditions, I suggest that the 3D editing process contain more objectivity by visualizing the depth data applied in some composition work such as Disparity map, Depth map, and the current 3D editing process. The proposed process has been used in the music drama , comparing with those of the film . The 3D values could be checked among cuts which have been changed a lot since those of , while the 3D value of drew an equal result in general. Since the current process is based on an artist's subjective sense of 3D, it could be changed according to the condition and state of the artist. Furthermore, it is impossible for us to predict the positive range, so it is apprehended that the cubic effect of space might be perverted by showing each different 3D value according to cuts in the same space or a limited space. On the other hand, the objective 3D editing by applying the visualization of depth data can adjust itself to the cubic effect of the same space and the whole content equally, which will enrich the 3D contents. It will even be able to solve some problems such as distortion of cubic effect and visual fatigue, etc.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.53-53
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• 2015

Agrobacterium tumefaciens-mediated transformation(ATMT) of Flammulina velutipes was used to produce a diverse number of transformants to discover the functions of gene that is vital for its variation color, spore pattern and cellulolytic activity. Futhermore, the transformant pool will be used as a good genetic resource for studying gene functions. Agrobacterium-mediated transformation was conducted in order to generate intentional mutants of F. velutipes strain KACC42777. Then Agrobacterium tumefaciens AGL-1 harboring pBGgHg was transformed into F. velutipes. This method is use to determine the functional gene of F. velutipes. Inverse PCR was used to insert T-DNA into the tagged chromosomal DNA segments and conducting sequence analysis of the F. velutipes. But this experiment had trouble in diverse morphological mutants because of dikaryotic nature of mushroom. It needed to make monokaryotic fruiting varients which introduced genes of compatible mating types. In this study, next generation sequencing data was generated from 28 strains of Flammulina velutipes with different phenotypes using Illumina Hiseq platform. Filtered short reads were initially aligned to the reference genome (KACC42780) to construct a SNP matrix. And then we built a phylogenetic tree based on the validated SNPs. The inferred tree represented that white- and brown- fruitbody forming strains were generally separated although three brown strains, 4103, 4028, and 4195, were grouped with white ones. This topological relationship was consistently reappeared even when we used randomly selected SNPs. Group I containing 4062, 4148, and 4195 strains and group II containing 4188, 4190, and 4194 strains formed early-divergent lineages with robust nodal supports, suggesting that they are independent groups from the members in main clades. To elucidate the distinction between white-fruitbody forming strains isolated from Korea and Japan, phylogenetic analysis was performed using their SNP data with group I members as outgroup. However, no significant genetic variation was noticed in this study. A total of 28 strains of Flammulina velutipes were analyzed to identify the genomic regions responsible for producing white-fruiting body. NGS data was yielded by using Illumina Hiseq platform. Short reads were filtered by quality score and read length were mapped on the reference genome (KACC42780). Between the white- and brown fruitbody forming strains. There is a high possibility that SNPs can be detected among the white strains as homozygous because white phenotype is recessive in F. velutipes. Thus, we constructed SNP matrix within 8 white strains. SNPs discovered between mono3 and mono19, the parental monokaryotic strains of 4210 strain (white), were excluded from the candidate. If the genotypes of SNPs detected between white and brown strains were identical with those in mono3 and mono19 strains, they were included in candidate as a priority. As a result, if more than 5 candidates SNPs were localized in single gene, we regarded as they are possibly related to the white color. In F. velutipes genome, chr01, chr04, chr07,chr11 regions were identified to be associated with white fruitbody forming. White and Brown Fruitbody strains can be used as an identification marker for F. veluipes. We can develop some molecular markers to identify colored strains and discriminate national white varieties against Japanese ones.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.98-106
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• 2009

This work proposes a 1280-RGB $\times$ 800-Dot 70.78mW 0.l3um CMOS LCD driver IC (LDI) for high-performance 16M-color low temperature poly silicon (LTPS) thin film transistor liquid crystal display (TFT-LCD) systems such as ultra mobile PC (UMPC) and mobile applications simultaneously requiring high resolution, low power, and small size at high speed. The proposed LDI optimizes power consumption and chip area at high resolution based on a resistor-string based architecture. The single column driver employing a 1:12 MUX architecture drives 12 channels simultaneously to minimize chip area. The implemented class-AB amplifier achieves a rail-to-rail operation with high gain and low power while minimizing the effect of offset and output deviations for high definition. The supply- and temperature-insensitive current reference is implemented on chip with a small number of MOS transistors. A slew enhancement technique applicable to next-generation source drivers, not implemented on this prototype chip, is proposed to reduce power consumption further. The prototype LDI implemented in a 0.13um CMOS technology demonstrates a measured settling time of source driver amplifiers within 1.016us and 1.072us during high-to-low and low-to-high transitions, respectively. The output voltage of source drivers shows a maximum deviation of 11mV. The LDI with an active die area of $12,203um{\times}1500um$ consumes 70.78mW at 1.5V/5.5V.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• Journal of Plant Biotechnology
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• v.39 no.1
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• pp.33-48
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• 2012

As a scientific curiosity to understand the structure and the function of crops and experimental efforts to apply it to plant breeding, genetic maps have been constructed in various crops. Especially, in the case of Brassica crop, genetic mapping has been accelerated since genetic information of model plant $Arabidopsis$ was available. As a result, the whole $B.$ $rapa$ genome (A genome) sequencing has recently been done. The genome sequences offer opportunities to develop molecular markers for genetic analysis in $Brassica$ crops. RFLP markers are widely used as the basis for genetic map construction, but detection system is inefficiency. The technical efficiency and analysis speed of the PCR-based markers become more preferable for many form of $Brassica$ genome study. The massive sequence informative markers such as SSR, SNP and InDels are also available to increase the density of markers for high-resolution genetic analysis. The high density maps are invaluable resources for QTLs analysis, marker assisted selection (MAS), map-based cloning and comparative analysis within $Brassica$ as well as related crop species. Additionally, the advents of new technology, next-generation technique, have served as a momentum for molecular breeding. Here we summarize genetic and genomic resources and suggest their applications for the molecular breeding in $Brassica$ crop.

• Journal of Science Education
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• v.44 no.1
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• pp.92-111
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• 2020

The 2015 revised science curriculum and NGSS (Next Generation Science Standard) suggest computational thinking as an inquiry skill or competency. Particularly, concern in computational thinking has increased since the Ministry of Education has required software education since 2014. However, there is still insufficient discussion on how to integrate computational thinking in science education. Therefore, this study aims to prepare a way to integrate computational thinking elements into scientific inquiry by analyzing the related literature. In order to achieve this goal, we summarized various definitions of the elements of computational thinking and analyzed general problem solving process and scientific inquiry process to develop and suggest the model. We also considered integrated problem solving cases from the computer science field and summarized the elements of the Computational Thinking-Scientific Inquiry (CT-SI) model. We asked scientists to explain their research process based on the elements. Based on these explanations from the scientists, we developed 'Problem-finding' CT-SI model and 'Problem solving' CT-SI model. These two models were reviewed by scientists. 'Problem-finding' model is relevant for selecting information and analyzing problems in the theoretical research. 'Problem solving' is suitable for engineering problem solving process using a general research process and engineering design. In addition, two teachers evaluated whether these models could be used in the secondary school curriculum. The models we developed in this study linked with the scientific inquiry and this will help enhance the practices of 'collecting, analyzing and interpreting data,' 'use of mathematical thinking and computer' suggested in the 2015 revised curriculum.