• Smart Structures and Systems
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• 제14권1호
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Smart Structures and Systems
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• 제18권5호
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

• Asian Pacific Journal of Cancer Prevention
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• 제13권10호
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• pp.4905-4908
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• 2012

Aim: Glioma cancer is the most common type of adult brain tumor. Recent genome-wide association studies (GWAS) have identified various new susceptibility regions and here we conducted an extensive analysis of associations between 12 single nucleotide polymorphisms (SNPs) and glioma risk. Methods: A total of 197 glioma cases and 197 health controls were selected, and 9 SNPs in 8 genes were analyzed using the Sequenom MassARRAY platform and Sequenom Assay Design 3.1 software. Results: We found the MAF among selected controls were consistent with the MAF from the NCBI SNP database. Among 9 SNPs in 8 genes, we identified four significant SNP genotypes associated with the risk of glioma, C/C genotype at rs730437 and T/T genotype at rs1468727 in ERGF were protective against glioma, whereas the T/T genotype at rs1799782 in XRCC1 and C/C genotype at rs861539 in XRCC3 conferred elevated risk. Conclusion: Our comprehensive analysis of nine SNPs in eight genes suggests that the rs730437 and rs1468727 in ERGF, rs1799782 in XRCC1 gene, and rs861539 in XRCC3 gene are associated with glioma risk. These findings indicate that genetic variants of various genes play a complex role in the development of glioma.

• 한국정보통신학회논문지
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• 제16권7호
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• pp.1335-1343
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• 2012

대양을 항해하는 선박의 안전 운항을 확보하기 위해 선박 항해시스템 및 선박 자동식별 장치 등의 장비가 기존 선박에 운용되고 있으나, 해상 교통량 증가에 따른 선박 사고는 증가하는 추세에 있다. 이러한 선박 사고는 항해자 및 승무원 등의 인적 오류에 의한 운항과실이 주된 요인으로 파악되었으며 이에 따른 해양사고를 미연에 방지하기 위한 기술이 필요한 실정이다. 따라서 본 논문에서는 선박 내 항해 및 운항자의 안전 운항을 감시하고 체계적인 관리를 위한 승무원 운용상황 감시 및 관리 시스템을 제안하고, 운항 안전을 위한 통합감시 플랫폼 설계와 승무원 휴대 상태계측 장치 및 휴대 단말시스템을 구현하였다. 또한 이를 통해 통합 안전 정보들의 상호 운용 가능성을 확인할 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.849-852
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• 2013

최근 발효식품이 건강식으로 대두되면서 발효식품에 대한 사람들의 관심이 증가되고 있다. 발효식품의 맛, 건강 기능성 및 저장성 등에 영향을 주는 요소들은 발효 재료, 온도, 습도 pH 등이 있으며, 숙성도를 나타내는 지표는 여러 가지가 있으며 그 중에서 pH 변화에 대한 모델 식은 아직 정립이 되지 않았다. 또한 식품 관리자나 소비자 입장에서는 발효 식품에 대한 숙성도 및 품질 상태를 알 수 있다면 발효 식품의 신뢰성이 높아지고 소비성도 높아질 것이다. 그러므로 본 논문에서는 발효 식품의 pH를 측정하여 회귀방정식을 이용하여 모델식을 구하여 발효 식품의 숙성도를 구하는데 플랫폼을 제공한다. 제안된 모델 식의 유용성을 확인하기 위해서 대표적인 발효식품 중 하나인 김치와 막걸리를 사용한 실험을 실시하였다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2017년도 춘계 종합학술대회 논문집
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• pp.105-106
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• 2017

Background: Atopic dermatitis one of the most common chronic skin diseases, is caused by various environmental and genetic factors. Methods: A total of 2609 healthy newborns who were enrolled in the COCOA study (COCOA) from 2008 to 2015 were surveyed for indoor environmental exposure to fungi during gestation and then diagnosed postnatally for atopic dermatitis. The fungi collected during the gestation of 20 normal subjects and 20 infants that developed atopic dermatitis were identified using Illumina's MiSeq platform and analyzed for their diversity and species. Results: A total of 2,609 respondents were surveyed (52.8% male and 47.2% female) Children, 1, 2, and 3 years old diagnosed with atopic dermatitis comprised 15.2%, 15.7%, and 14.1% of the respondents, respectively. The prevalence of exposure to mold during gestation was 1.46 (95% CI, 1.05-2.04) and 1.52 (95% CI, 0.95-2.43), in the first and third years after birth, respectively. One-year-old children with atopic dermatitis and no fungal markers detected in the bathroom environment during gestation accounted for less than 5% (aOR, 1.51; 95%CI, 0.96-2.38) and in the group less than 5 ~ 30% (aOR, 2.21; 95%CI, 1.00-4.89), 3-year-old children had an increased prevalence of atopic dermatitis of more than 30% (aOR, 9.48, 95%CI 1.42-63.13). Conclusions: Exposure to indoor fungi during gestation and infancy is associated with the development of atopic dermatitis in children. The phyla and genera of the fungi in the indoor house dust differed during gestation. This suggests that exposure to indoor fungi during gestation may be associated with the development of atopic dermatitis in children. Future research will be necessary to establish the underlying mechanisms.

• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2001년도 Proceedings of 2001 International Symposium
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• pp.155-157
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• 2001

Bifidobacterium spp. is nonpathogenic, gram-positive and anaerobic bacteria, which inhabit the intestinal tract of humans and animals. In breast-fed infants, bifidobacteria comprise morethan 90％ of the gut bacterial population. Bifidobacteria spp. are used in commericial fermented dairy products and have been suggested to exert health promoting effects on the host by maintaining intestinal microflora balances, improving lactose tolerance, reducing serum cholesterol levels, increasing synthesis of vitamins, and aiding the immune enchancement and anticarcinogenic activity for the host. These beneficial effects of Bifidobacterium are strain-related. Therefore continued efforts to improve strain characteristics are warranted. in these respect, development of vector system for Bifidobacterium is very important not only for the strain improvement but also because Bifidobacterium is most promising in serving as a delivery system for the useful gene products, such as vaccine or anticarcinogenic polypeptides, into human intestinal tract. For developing vector system, we have characterized several bifidobacterial plasmids at genetic level and developed several shuttle vectors between E. coli and Bifidobacterium using them. Also, we have cloned and sequenced several metabolic genes and food grade selection marker. Also we have obtained bifidobacterial surface protein, which will be used as the mediator for surface display of foreign genes. Recently we have succeeded in expressing amylase and GFP in Bifidobacterium using our own expression vector system. Now we are in a very exciting stage for the molecular breeding and safe delivery system using probiotic Bifidobacterium strains.

• Journal of Plant Biotechnology
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• 제43권3호
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• pp.302-310
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• 2016

A study aimed at identifying putative drought responsive genes that confer tolerance to water stress deficit in tea plants was conducted in a 'rain-out shelter' using potted plants. Eighteen months old drought tolerant and susceptible tea cultivars were each separately exposed to water stress or control conditions of 18 or 34% soil moisture content, respectively, for three months. After the treatment period, leaves were harvested from each treatment for isolation of RNA and cDNA synthesis. The cDNA libraries were sequenced on Roche 454 high-throughput pyrosequencing platform to produce 232,853 reads. After quality control, the reads were assembled into 460 long transcripts (contigs). The annotated contigs showed similarity with proteins in the Arabidopsis thaliana proteome. Heat shock proteins (HSP70), superoxide dismutase (SOD), catalase (cat), peroxidase (PoX), calmodulinelike protein (Cam7) and galactinol synthase (Gols4) droughtrelated genes were shown to be regulated differently in tea plants exposed to water stress. HSP70 and SOD were highly expressed in the drought tolerant cultivar relative to the susceptible cultivar under drought conditions. The genes and pathways identified suggest efficient regulation leading to active adaptation as a basal defense response against water stress deficit by tea. The knowledge generated can be further utilized to better understand molecular mechanisms underlying stress tolerance in tea.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1306-1325
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• 2019

As the world is moving towards digitization, data is generated from various sources at a faster rate. It is getting humungous and is termed as big data. The financial sector is one domain which needs to leverage the big data being generated to identify financial risks, fraudulent activities, and so on. The design of predictive models for such financial big data is imperative for maintaining the health of the country's economics. Financial data has many features such as transaction history, repayment data, purchase data, investment data, and so on. The main problem in predictive algorithm is finding the right subset of representative features from which the predictive model can be constructed for a particular task. This paper proposes a correlation-based method using submodular optimization for selecting the optimum number of features and thereby, reducing the dimensions of the data for faster and better prediction. The important proposition is that the optimal feature subset should contain features having high correlation with the class label, but should not correlate with each other in the subset. Experiments are conducted to understand the effect of the various subsets on different classification algorithms for loan data. The IBM Bluemix BigData platform is used for experimentation along with the Spark notebook. The results indicate that the proposed approach achieves considerable accuracy with optimal subsets in significantly less execution time. The algorithm is also compared with the existing feature selection and extraction algorithms.

• 한국정보통신학회논문지
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• 제18권6호
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• pp.1475-1480
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• 2014

Fitness 센터 이용자들은 자신에게 맞지 않은 기구를 선택함으로써 부상의 위험이 존재했고 효율적인 운동 방법을 익히기 위해서는 오랜 시간이 필요했다. 이를 해결하기 위해 사람들은 퍼스널 트레이닝을 이용하지만 값비싼 비용의 문제가 발생하고 혼자 운동하는 습관을 기르는데 어려움을 갖게 했다. 본 논문에서는 다양한 스마트 폰 플랫폼과 호환성을 가진 하이브리드 앱 기반으로 개인화된 트레이닝 마켓 시스템을 구축하였다. 사용자들은 Fitness 센터에서 자신의 운동 기록을 스마트 폰의 하이브리드 앱을 활용해 가속도 센서를 활용하여 입력하거나 직접 입력하는 방식으로 웹에 전송한다. 이를 기반으로 사용자들에게 맞는 운동 프로그램을 웹에 있는 트레이닝 마켓을 통해 제공하게 된다. 퍼스널 트레이닝 마켓에는 다양한 사용자들이 운동 기록을 확인하여 그에 대한 운동 프로그램을 추천할 수 있고 스스로 선택하여 적용할 수 있다. 이를 통해 사용자는 자신에게 맞는 운동 프로그램으로 장기간 운동할 수 있는 습관을 기를 수 있고 능동적인 목표 설정이 가능하다.