• 제목/요약/키워드: advanced models

검색결과 1,828건 처리시간 0.03초

Clinical and Neurobiological Relevance of Current Animal Models of Autism Spectrum Disorders

  • Kim, Ki Chan;Gonzales, Edson Luck;Lazaro, Maria T.;Choi, Chang Soon;Bahn, Geon Ho;Yoo, Hee Jeong;Shin, Chan Young
    • Biomolecules & Therapeutics
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    • 제24권3호
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    • pp.207-243
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    • 2016
  • Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication impairments, as well as repetitive and restrictive behaviors. The phenotypic heterogeneity of ASD has made it overwhelmingly difficult to determine the exact etiology and pathophysiology underlying the core symptoms, which are often accompanied by comorbidities such as hyperactivity, seizures, and sensorimotor abnormalities. To our benefit, the advent of animal models has allowed us to assess and test diverse risk factors of ASD, both genetic and environmental, and measure their contribution to the manifestation of autistic symptoms. At a broader scale, rodent models have helped consolidate molecular pathways and unify the neurophysiological mechanisms underlying each one of the various etiologies. This approach will potentially enable the stratification of ASD into clinical, molecular, and neurophenotypic subgroups, further proving their translational utility. It is henceforth paramount to establish a common ground of mechanistic theories from complementing results in preclinical research. In this review, we cluster the ASD animal models into lesion and genetic models and further classify them based on the corresponding environmental, epigenetic and genetic factors. Finally, we summarize the symptoms and neuropathological highlights for each model and make critical comparisons that elucidate their clinical and neurobiological relevance.

Systems-Level Analysis of Genome-Scale In Silico Metabolic Models Using MetaFluxNet

  • Lee, Sang-Yup;Woo, Han-Min;Lee, Dong-Yup;Choi, Hyun-Seok;Kim, Tae-Yong;Yun, Hong-Seok
    • Biotechnology and Bioprocess Engineering:BBE
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    • 제10권5호
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    • pp.425-431
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    • 2005
  • The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

상용 미분탄 보일러 연소해석에서 석탄 탈휘발 모델 및 난류반응속도의 영향 평가 (Effects of coal devolatilization model and turbulent reaction rate in numerical simulations of a large-scale pulverized-coal-fired boiler)

  • 양주향;김정은;류창국
    • 한국연소학회:학술대회논문집
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    • 한국연소학회 2014년도 제49회 KOSCO SYMPOSIUM 초록집
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    • pp.59-62
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    • 2014
  • Predicting coal combustion by computational fluid dynamics (CFD) requires a combination of complicated flow and reaction models for turbulence, radiation, particle flows, heterogeneous combustion, and gaseous reactions. There are various levels of models available for each of the phenomena, but the use of advanced models are significantly restricted in a large-scale boiler due to the computational costs and the balance of accuracy between adopted models. In this study, the influence of coal devolatilization model and turbulent mixing rate was assessed in CFD for a commercial boiler at 500 MWe capacity. For coal devolatilization, two models were compared: i) a simple model assuming single volatile compound based on proximate analysis and ii) advanced model of FLASHCHAIN with multiple volatile species. It was found out that the influence of the model was observed near the flames but the overall gas temperature and heat transfer rate to the boiler were very similar. The devolatilization rate was found not significant since the difference in near-flame temperature became noticeable when it was multiplied by 10 or 0.1. In contrast, the influence of turbulent mixing rate (constant A in the Magnussen model) was found very large. Considering the heat transfer rate and flame temperature, a value of 1.0 was recommended for the rate constant.

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Review of the Existing Relative Biological Effectiveness Models for Carbon Ion Beam Therapy

  • Kim, Yejin;Kim, Jinsung;Cho, Seungryong
    • 한국의학물리학회지:의학물리
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    • 제31권1호
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    • pp.1-7
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    • 2020
  • Hadron therapy, such as carbon and helium ions, is increasingly coming to the fore for the treatment of cancers. Such hadron therapy has several advantages over conventional radiotherapy using photons and electrons physically and clinically. These advantages are due to the different physical and biological characteristics of heavy ions including high linear energy transfer and Bragg peak, which lead to the reduced exit dose, lower normal tissue complication probability and the increased relative biological effectiveness (RBE). Despite the promising prospects on the carbon ion radiation therapy, it is in dispute with which bio-mathematical models to calculate the carbon ion RBE. The two most widely used models are local effect model and microdosimetric kinetic model, which are actively utilized in Europe and Japan respectively. Such selection on the RBE model is a crucial issue in that the dose prescription for planning differs according to the models. In this study, we aim to (i) introduce the concept of RBE, (ii) clarify the determinants of RBE, and (iii) compare the existing RBE models for carbon ion therapy.

Comparative study of constitutive relations implemented in RELAP5 and TRACE - Part II: Wall boiling heat transfer

  • Shin, Sung Gil;Lee, Jeong Ik
    • Nuclear Engineering and Technology
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    • 제54권5호
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    • pp.1860-1873
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    • 2022
  • Nuclear thermal-hydraulic system analysis codes have been developed to comprehensively model nuclear reactor systems to evaluate the safety of a nuclear reactor system. For analyzing complex systems with finite computational resources, system codes usually solve simplified fluid equations for coarsely discretized control volumes with one-dimensional assumptions and replace source terms in the governing equations with constitutive relations. Wall boiling heat transfer models are regarded as essential models in nuclear safety evaluation among many constitutive relations. The wall boiling heat transfer models of two widely used nuclear system codes, RELAP5 and TRACE, are analyzed in this study. It is first described how wall heat transfer models are composed in the two codes. By utilizing the same method described in Part 1 paper, heat fluxes from the two codes are compared under the same thermal-hydraulic conditions. The significant factors for the differences are identified as well as at which conditions the non-negligible difference occurs. Steady-state simulations with both codes are also conducted to confirm how the difference in wall heat transfer models impacts the simulation results.

Where and Why? A Novel Approach for Prioritizing Implementation Points of Public CCTVs using Urban Big Data

  • Ji Hye Park;Daehwan Kim;Keon Chul Park
    • 인터넷정보학회논문지
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    • 제24권5호
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    • pp.97-106
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    • 2023
  • Citizens' demand for public CCTVs continues to rise, along with an increase in variouscrimes and social problems in cities. In line with the needs of citizens, the Seoul Metropolitan Government began installing CCTV cameras in 2010, and the number of new installations has increased by over 10% each year. As the large surveillance system represents a substantial budget item for the city, decision-making on location selection should be guided by reasonable standards. The purpose of this study is to improve the existing related models(such as public CCTV priority location analysis manuals) to establish the methodology foranalyzing priority regions ofSeoul-type public CCTVs and propose new mid- to long-term installation goals. Additionally, using the improved methodology, we determine the CCTV priority status of 25 autonomous districts across Seoul and calculate the goals. Through its results, this study suggests improvements to existing models by addressing their limitations, such as the sustainability of input data, the conversion of existing general-purpose models to urban models, and the expansion of basic local government-level models to metropolitan government levels. The results can also be applied to other metropolitan areas and are used by the Seoul Metropolitan Government in its CCTV operation policy

Design and Implementation of AI Recommendation Platform for Commercial Services

  • Jong-Eon Lee
    • International journal of advanced smart convergence
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    • 제12권4호
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    • pp.202-207
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    • 2023
  • In this paper, we discuss the design and implementation of a recommendation platform actually built in the field. We survey deep learning-based recommendation models that are effective in reflecting individual user characteristics. The recently proposed RNN-based sequential recommendation models reflect individual user characteristics well. The recommendation platform we proposed has an architecture that can collect, store, and process big data from a company's commercial services. Our recommendation platform provides service providers with intuitive tools to evaluate and apply timely optimized recommendation models. In the model evaluation we performed, RNN-based sequential recommendation models showed high scores.

Analysis of AI Model Hub

  • Yo-Seob Lee
    • International Journal of Advanced Culture Technology
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    • 제11권4호
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    • pp.442-448
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    • 2023
  • Artificial Intelligence (AI) technology has recently grown explosively and is being used in a variety of application fields. Accordingly, the number of AI models is rapidly increasing. AI models are adapted and developed to fit a variety of data types, tasks, and environments, and the variety and volume of models continues to grow. The need to share models and collaborate within the AI community is becoming increasingly important. Collaboration is essential for AI models to be shared and improved publicly and used in a variety of applications. Therefore, with the advancement of AI, the introduction of Model Hub has become more important, improving the sharing, reuse, and collaboration of AI models and increasing the utilization of AI technology. In this paper, we collect data on the model hub and analyze the characteristics of the model hub and the AI models provided. The results of this research can be of great help in developing various multimodal AI models in the future, utilizing AI models in various fields, and building services by fusing various AI models.