• Journal of Communications and Networks
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• v.14 no.5
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.299-306
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• 2009

Followed by the popularity of the Internet, a number of access technologies to the Internet have been developed. EAP is an authentication framework. It is designed to provide the authentication functionality in the access network. Because of its flexibility and extensibility EAP poses a global solution for the authentication supported by many access networks. However, EAP has critical weaknesses in the protocol which may, in turn, decrease the EAP performance. Some of the weaknesses are caused by the "lock-step" flow control which only supports a single packet in flight. Considering the weaknesses, we propose a solution for the flow control. Using simulation we prove that our solutions improve the EAP performance.

• 한국환경농학회:학술대회논문집
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• 2011.07a
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• pp.196-204
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• 2011

Abiotic stress is the primary cause of crop loss worldwide, reducing average yields for most major crop plants by more than 50%. In addition, future agricultural production and management will encounter multifaceted challenges from global climate change. Therefore, it is necessary to study the molecular response of crop plants to the stresses in order to develop appropriate strategies to sustain food production under adverse environmental conditions. We carried out a large scale proteomic analysis of soybean plants in response to various abiotic stresses, including drought, salinity, waterlogging and their interactions. Proteins were analyzed by two dimensional polyacrylamide gel electrophoresis followed by matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry. The identified proteins are involved in a wide range of cellular functions. In addition to the well known stress-associated proteins, we identified several novel proteins, which were not reported before. In many cases our proteomic data bridges the gap between mRNA and metabolite data. Our studie provides new insights into identification of abiotic stress responsive proteins in soybean, and demonstrates the advantages of proteomic analysis in dissecting metabolic and regulatory networks.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.90.2-90.2
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• 2013

Vertically-aligned silicon nanostructure arrays (SNAs) have been drawing much attention due to their useful electrical properties, large surface area, and quantum confinement effect. SNAs are typically fabricated by chemical vapor deposition, reactive ion etching, or wet chemical etching. Recently, metal-assisted chemical etching process, which is relatively simple and cost-effective, in combination with nanosphere lithography was recently demonstrated for vertical SNA fabrication with controlled SNA diameters, lengths, and densities. However, this method exhibits limitations in terms of large-area preparation of unperiodic nanostructures and SNA geometry tuning independent of inter-structure separation. In this work, we introduced the layerby- layer deposition of polyelectrolytes for holding uniformly dispersed polystyrene beads as mask and demonstrated the fabrication of well-dispersed vertical SNAs with controlled geometric parameters on large substrates. Additionally, we present a new means of building in vitro neuronal networks using vertical nanowire arrays. Primary culture of rat hippocampal neurons were deposited on the bare and conducting polymer-coated SNAs and maintained for several weeks while their viability remains for several weeks. Combined with the recently-developed transfection method via nanowire internalization, the patterned vertical nanostructures will contribute to understanding how synaptic connectivity and site-specific perturbation will affect global neuronal network function in an extant in vitro neuronal circuit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4787-4807
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• 2016

Although the dense interconnection datacenter networks (DCNs) (e.g. FatTree) provide multiple paths and high bisection bandwidth for each server pair, the single-path TCP (SPT) and ECMP which are widely used currently neither achieve high bandwidth utilization nor have good load balancing. Due to only one available transmission path, SPT cannot make full use of all available bandwidth, while ECMP's random hashing results in many collisions. In this paper, we present OFPT, an OpenFlow based Parallel Transport framework, which integrates precise routing and scheduling for better load balancing and higher network throughput. By adopting OpenFlow based centralized control mechanism, OFPT computes the optimal path and bandwidth provision for each flow according to the global network view. To guarantee high throughput, OFPT dynamically schedules flows with Seamless Flow Migration Mechanism (SFMM), which can avoid packet loss in flow rerouting. Finally, we test OFPT on Mininet and implement it in a real testbed. The experimental results show that the average network throughput in OFPT is up to 97.5% of bisection bandwidth, which is higher than ECMP by 36%. Besides, OFPT decreases the average flow completion time (AFCT) and achieves better scalability.

• Annals of Geriatric Medicine and Research
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• v.20 no.3
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• pp.149-159
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• 2016

Background: Since the mid-20th century, the ways in which social networks and older adults' health are related have been widely studied. However, few studies investigate the relationship between self-rated health and position in a complete social network of one entire Korean rural village. This study highlights use of a complete network in health studies. Methods: Using the Korean Social Life and Health Project, the population-based data of adults aged 60 or older and their spouses in one myeon in Ganghwa island (Ganghwa-gun, Incheon, Korea), Incheon, Korea (with a 95% response rate), this study built a $1,012{\times}1,012$ complete social network matrix of the village. The data were collected from 2011 to 2012, and 731 older adults were analyzed. The ordered logistic models to predict self-rated health allowed us to examine social factors from socio-demographic to individual community activities, ego-centered network characteristics, and positions in a complete network. Results: From the network data, 5 network components were identified. Even after controlling for all other factors, if a respondent belonged to a segregated component, the probability that he or she reported good health dropped substantially. Additionally, high in-degree centrality was connected to greater self-rated health. Conclusion: This finding highlights the importance of social position not only from the respondents' point of view but also from the entire village's perspective. Even if a respondent maintained a large social network, when all of those social ties belonged to a segregated group in the village, the respondent's health suffered from this segregation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.281-286
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• 2009

The proposed technique uses cyclic frame structure, where three periods such as beacon period (BP), mesh contention access period (MCAP) and slotted period (SP) are in a data frame. This paper studies on a mechanism to allow communication nodes (6lowpan) in a PAN with different logical channel for global healthcare applications monitoring technology. The proposed super framework structure system has installed 6lowpan sensor nodes to communicate with each other. The basic idea is to time share logical channels to perform 6lowpan sensor node. The concept of 6lowpan sensor node and various biomedical sensors fixed on the patient BAN (Body Area Network) for monitoring health condition. In PAN (hospital area), has fixed gateways that received biomedical data from 6lowpan (patient). Each 6lowpan sensor node (patient) has IP-addresses that would be directly connected to the internet. With the help of IP-address service provider can recognize or analyze patient data from all over the globe by the internet service provider, with specific equipments i.e. cell phone, PDA, note book. The NS-2.33 result shows the performance of data transmission delay and data delivery ratio in the case of hop count in a PAN (Personal Area Networks).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.969-972
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• 2009

With the advent of the era of ubiquitous computing, the number of wireless communication devices has been exponentially increasing, which phenomenon requires for the preparation for the upcoming shortage of frequency resource. Recently, in consequence, the concept of Cognitive Radio (CR) was introduced in which the wireless nodes periodically recognize and learn the external conditions of communication including the usage of the frequency spectrum. It is essential to assure sufficient range of frequency to satisfy the users of the increasing wireless network devices. However, since not only the frequency band for wireless communication is finite, but most part of them had already been assigned for the primary users of the wireless network service, it is very difficult to ensure the band of frequency for additional communication service. In this contribution, we analyze and describe the issues of designing and implementation of CR networks.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.123-123
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• 2019

최근 기후변화로 인해 중국, 한국, 일본, 몽골 등을 포함한 동아시아 지역은 태풍, 가뭄, 홍수와 같은 자연재해의 발생 빈도가 증가하고 있는 추세이다. 중국의 경우 2017년 극심한 가뭄으로 1,850만 (ha)의 농작물 피해가 발생하였으며, 몽골 또한 2017년 4월 이후 극심한 가뭄으로 사막화가 급속도로 진행되고 있다. 위성 기반의 강우 자료는 공간과 시간 해상도가 높아짐에 따라 지상관측소 강수량 자료의 대체 수단으로 이용되고 있다. 본 연구에서는 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC) 강우 위성 자료를 활용하여 기상학적 가뭄지수인 표준강수지수 (Standardized Precipitation Index, SPI)를 산정하였다. 시간 해상도는 월별 영상을 기준으로 2008년부터 2017년까지 지난 10년간의 데이터를 이용하였으며, 각각 격자가 다른 위성영상을 기존 기상관측소와 비교하였다. 피어슨 상관계수 (Pearson Correlation Coefficient, R)를 활용하여 강우 위성 영상과 지상관측소의 상관관계를 분석하고, 평균절대오차 (Mean Absolute Error, MAE), 평균제곱근오차 (Root Mean Square Error, RMSE)를 통해 통계적으로 정확도를 분석하였다. 인공위성 강수량 자료는 미계측 지역이 많은 곳이나 측정이 불가능한 지역에 효율성 측면에서 중요한 이점을 제공할 것으로 판단된다.