• Title/Summary/Keyword: data-driven model

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Technology Development Strategy of Piggyback Transportation System Using Topic Modeling Based on LDA Algorithm

  • Jun, Sung-Chan;Han, Seong-Ho;Kim, Sang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.261-270
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    • 2020
  • In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

A semi-supervised interpretable machine learning framework for sensor fault detection

  • Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.251-266
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    • 2022
  • Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

A Policy-Based Meta-Planning for General Task Management for Multi-Domain Services (다중 도메인 서비스를 위한 정책 모델 주도 메타-플래닝 기반 범용적 작업관리)

  • Choi, Byunggi;Yu, Insik;Lee, Jaeho
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.12
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    • pp.499-506
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    • 2019
  • An intelligent robot should decide its behavior accordingly to the dynamic changes in the environment and user's requirements by evaluating options to choose the best one for the current situation. Many intelligent robot systems that use the Procedural Reasoning System (PRS) accomplishes such task management functions by defining the priority functions in the task model and evaluating the priority functions of the applicable tasks in the current situation. The priority functions, however, are defined locally inside of the plan, which exhibits limitation for the tasks for multi-domain services because global contexts for overall prioritization are hard to be expressed in the local priority functions. Furthermore, since the prioritization functions are not defined as an explicit module, reuse or extension of the them for general context is limited. In order to remove such limitations, we propose a policy-based meta-planning for general task management for multi-domain services, which provides the ability to explicitly define the utility of a task in the meta-planning process and thus the ability to evaluate task priorities for general context combining the modular priority functions. The ontological specification of the model also enhances the scalability of the policy model. In the experiments, adaptive behavior of a robot according to the policy model are confirmed by observing the appropriate tasks are selected in dynamic service environments.

Development of an Efficient Method to Evaluate the Optimal Location of Groundwater Dam (최적의 지하댐 입지 선정을 위한 효율적 평가 방법 개발)

  • Jeong, Jina;Park, Eungyu
    • Economic and Environmental Geology
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    • v.53 no.3
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    • pp.245-258
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    • 2020
  • In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

Numerical Model for Spreading of Cochlodinium Bloom in the Southern Coastal Waters in Korea (한국 남해안에서 Cochlodinium적조 확산모델)

  • Kwon Chul Hui;Cho Ku Dae
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.35 no.6
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    • pp.568-577
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    • 2002
  • The spreading Cocuoainim polykikoides bloom in the southern coastal waters of Korea was simulated using numerical model including the physical processes of water flow and the chemical processes of increasing cell of C. polykikoides by uptake of dissolved nutrients. The circulation of sea water was simulated by two dimensional tide model reflecting the main four tidal components of $M_2,\;S_2,\;K_1,\;O_1$, and permanent current was driven by inflow/outflow across open boundaries. According to the result of model which tidal and permanent current were reflected simultaneously, eastward flows entering the southern waters from the western waters of Korea are dominant but westward flows are weak relatively. These result suggest that it is difficult for initial C. polykikoides bloom generated in the coastal waters of Goheung to move to the western coast of Korea through Jeju Strait. For spreading model of C. poiyhikoides, the range of generating distribution and the generating time of C. polykikoides bloom in coastal area are similar to those of observation data in the field. Wind is the most important factor in moving and distribution of red tide. Permanent current flowing eastward is also considered to be important factor and tidal current was a little influenced.

Population Characteristics Influencing Treatment Service Use among Individuals with Drug Dependency (마약류 의존자 치료재활 서비스 이용에 영향을 미치는 개인적 특성에 관한 연구)

  • Kim, Nang-hee
    • Korean Journal of Social Welfare Studies
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    • no.39
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    • pp.395-423
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    • 2008
  • This study investigated population characteristics that influencing treatment service use of people who are voluntarily using drug dependency treatment services by using logistic and hierarchical regression analysis. The research model of the current study was driven by the framework of the 'the Behavioral Model of Health Services Use(the Andersen model)' that has been broadly applied to study on health behavior. This study used data from a sample group of 80 adults by using purposive sampling. This study found that some predisposing factors, enabling factors and need factors have direct effects on service use. In detail, individuals who graduated from high school use drug dependency treatment utilities more than those who did not. Further, individuals who were given more support from family, peers, or others, use the treatment utilities more frequently and were more willing to use the utilities continuously. Furthermore, the greater the perceived need felt by the dependent, the greater the tendency to enter hospitals or shelters. The important implications of this study for social work practice and social policy can be summarized as follows: first, this study supports the idea that intervention for drug dependents in Korea should be focused on environment resources rather than population characteristics; and government must support drug dependent treatment systems; the present study was the first to investigate Korean drug dependents through taking a more positive view, as well as the first to apply 'the Behavioral Model of Health Services Use', and as such represents an example of how studies could be productively conducted in the future. Despite these implications, there remain some limitations in this study. These include the following: limitation in generalizability of the results; the cross-sectional nature of the study design; survey research through the questionnaire method; using foreign scales; and the difficulty of classifying treatment settings.

Parameter Optimization and Uncertainty Analysis of the NWS-PC Rainfall-Runoff Model Coupled with Bayesian Markov Chain Monte Carlo Inference Scheme (Bayesian Markov Chain Monte Carlo 기법을 통한 NWS-PC 강우-유출 모형 매개변수의 최적화 및 불확실성 분석)

  • Kwon, Hyun-Han;Moon, Young-Il;Kim, Byung-Sik;Yoon, Seok-Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4B
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    • pp.383-392
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    • 2008
  • It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

Gramene database: A resource for comparative plant genomics, pathways and phylogenomics analyses

  • Tello-Ruiz, Marcela K.;Stein, Joshua;Wei, Sharon;Preece, Justin;Naithani, Sushma;Olson, Andrew;Jiao, Yinping;Gupta, Parul;Kumari, Sunita;Chougule, Kapeel;Elser, Justin;Wang, Bo;Thomason, James;Zhang, Lifang;D'Eustachio, Peter;Petryszak, Robert;Kersey, Paul;Lee, PanYoung Koung;Jaiswal, kaj;Ware, Doreen
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2017.06a
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    • pp.135-135
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    • 2017
  • The Gramene database (http://www.gramene.org) is a powerful online resource for agricultural researchers, plant breeders and educators that provides easy access to reference data, visualizations and analytical tools for conducting cross-species comparisons. Learn the benefits of using Gramene to enrich your lectures, accelerate your research goals, and respond to your organismal community needs. Gramene's genomes portal hosts browsers for 44 complete reference genomes, including crops and model organisms, each displaying functional annotations, gene-trees with orthologous and paralogous gene classification, and whole-genome alignments. SNP and structural diversity data, available for 11 species, are displayed in the context of gene annotation, protein domains and functional consequences on transcript structure (e.g., missense variant). Browsers from multiple species can be viewed simultaneously with links to community-driven organismal databases. Thus, while hosting the underlying data for comparative studies, the portal also provides unified access to diverse plant community resources, and the ability for communities to upload and display private data sets in multiple standard formats. Our BioMart data mining interface enable complex queries and bulk download of sequence, annotation, homology and variation data. Gramene's pathway portal, the Plant Reactome, hosts over 240 pathways curated in rice and inferred in 66 additional plant species by orthology projection. Users may compare pathways across species, query and visualize curated expression data from EMBL-EBI's Expression Atlas in the context of pathways, analyze genome-scale expression data, and conduct pathway enrichment analysis. Our integrated search database and modern user interface leverage these diverse annotations to facilitate finding genes through selecting auto-suggested filters with interactive views of the results.

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Estimation and assessment of natural drought index using principal component analysis (주성분 분석을 활용한 자연가뭄지수 산정 및 평가)

  • Kim, Seon-Ho;Lee, Moon-Hwan;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.49 no.6
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    • pp.565-577
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    • 2016
  • The objective of this study is to propose a method for computing the Natural Drought Index (NDI) that does not consider man-made drought facilities. Principal Component Analysis (PCA) was used to estimate the NDI. Three monthly moving cumulative runoff, soil moisture and precipitation were selected as input data of the NDI during 1977~2012. Observed precipitation data was collected from KMA ASOS (Korea Meteorological Association Automatic Synoptic Observation System), while model-driven runoff and soil moisture from Variable Infiltration Capacity Model (VIC Model) were used. Time series analysis, drought characteristic analysis and spatial analysis were used to assess the utilization of NDI and compare with existing SPI, SRI and SSI. The NDI precisely reflected onset and termination of past drought events with mean absolute error of 0.85 in time series analysis. It explained well duration and inter-arrival time with 1.3 and 1.0 respectively in drought characteristic analysis. Also, the NDI reflected regional drought condition well in spatial analysis. The accuracy rank of drought onset, termination, duration and inter-arrival time was calculated by using NDI, SPI, SRI and SSI. The result showed that NDI is more precise than the others. The NDI overcomes the limitation of univariate drought indices and can be useful for drought analysis as representative measure of different types of drought such as meteorological, hydrological and agricultural droughts.

Business relocation grant policies and manufacturing establishments' relocations to non-Seoul metropolitan areas (기업의 지방 이전 보조금 지원 제도와 관련한 수도권 제조업체의 비수도권 이동 확률 변화 분석)

  • Yi, Yoojin;Kim, Euijune
    • Journal of the Korean Regional Science Association
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    • v.33 no.3
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    • pp.61-78
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    • 2017
  • Among several policies for industrial decentralization introduced since the 1960s, business relocation grant policies put a heavy financial burden on central and local governments. This study investigates the change in the likelihood of manufacturing establishments' relocation to the non-SMA associate with the change in business relocation grant policies. Using the mining and manufacturing survey data from 1996 to 2014, manufacturing firms' relocation decision model in nested logit structure was estimated. The data showed that the proportion of movements from the SMA to the non-SMA significantly increased after the introduction of the grant policies. However, estimation results of firms' relocation decision model indicated that the likelihood of firms relocating from the SMA to the non-SMA decreased after the introduction of the grant policies. In particular, firms' likelihood to move into the rural regions is even lower in the period of the grant extension. This suggests that increasing rate of relocations toward the rural regions may have been driven by the growing advantage of rural locations, such as low land rent and improvement in market accessibility, rather than the grants per se. This implies that the alleviation of physical and environmental constraints of the rural regions and the creation of business friendly environment such as easy access to premises at reasonable prices and strengthened linkage with the SMA, rather than simple provision of business relocation grants, needed to attract businesses in the rural regions.