• ETRI Journal
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• 제43권5호
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• pp.825-834
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• 2021

Based on its simplicity and user-friendly characteristics, OpenMP has become the standard model for programming on shared-memory architectures. Checkpointing-aided parallel execution (CAPE) is an approach that utilizes the discontinuous incremental checkpointing technique (DICKPT) to translate and execute OpenMP programs on distributed-memory architectures automatically. Currently, CAPE implements the OpenMP execution model by utilizing the DICKPT to distribute parallel jobs and their data to slave machines, and then collects the results after executing these distributed jobs. Although this model has been proven to be effective in terms of performance and compatibility with OpenMP on distributed-memory systems, it cannot fully exploit the capabilities of multicore processors. This paper presents a novel execution model for CAPE that utilizes two levels of parallelism. In the proposed model, we add another level of parallelism in the form of multithreaded processes on slave machines with the goal of better exploiting their multicore CPUs. Initial experimental results presented near the end of this paper demonstrate that this model provides significantly enhanced CAPE performance.

• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1305-1316
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• 2018

Graphical user interface(GUI) has a very important role to interact with software users. However, designing and coding of GUI are tedious and pain taking processes. In many studies, the researchers are trying to convert GUI elements or widgets to code or describe formally their structures by help of domain knowledge of stochastic methods. In this paper, we propose the GUI elements detection approach based on object detection strategy using deep neural networks(DNN). Object detection with DNN is the approach that integrates localization and classification techniques. From the experimental result, if we selected the appropriate object detection model, the results can be used for automatic code generation from the sketch or capture images. The successful GUI elements detection can describe the objects as hierarchical structures of elements and transform their information to appropriate code by object description translator that will be studied at future.

• 방사성폐기물학회지
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• 제19권1호
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• pp.9-27
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• 2021

As an example of research activities in decontamination for decommissioning, new data are presented on the options for corrosion layer dissolution during the decommissioning decontamination, or persulfate regeneration for decontamination solutions re-use. For the management of spent decontamination solutions, new method based on solvent extraction of radionuclides into ionic liquid followed by electrodeposition of the radionuclides has been developed. Fields of applications of composite inorganic-organic absorbers or solid extractants with polyacrylonitrile (PAN) binding matrix for the treatment of liquid radioactive waste are reviewed; a method for americium separation from the boric acid containing NPP evaporator concentrates based on the TODGA-PAN material is discussed in more detail. Performance of a model of radionuclide transport, developed and implemented within the GoldSim programming environment, for the safety studies of the LLW/ILW repository is demonstrated on the specific case of the Richard repository (Czech Republic). Continuation and even broadening of these activities are expected in connection with the approaching end of the lifespan of the first blocks of the Czech NPPs.

• Bulletin of the Korean Chemical Society
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• 제22권4호
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• pp.337-348
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• 2001

This article gives an overview of a recently developed channel system, frit-inlet asymmetrical flow field-flow fractionation (FI-AFlFFF), which can be applied for the separation of nanoparticles, proteins, and water soluble polymers. A conventiona l asymmetrical flow FFF channel has been modified into a frit-inlet asymmetrical type by introducing a small inlet frit near the injection point and the system operation of the FI-AFlFFF channel can be made with a great convenience. Since sample components injected into the FI-AFlFFF channel are hydrodynamically relaxed, sample injection and separation processes proceed without interruption of the migration flow. Therefore in FI-AFlFFF, there is no requirement for a valve operation to switch the direction of the migration flow that is normally achieved during the focusing/relaxation process in a conventional asymmetrical channel. In this report, principles of the hydrodynamic relaxation in FI-AFlFFF channel are described with equations to predict the retention time and to calculate the complicated flow variations in the developed channel. The retention and resolving power of FI-AFlFFF system are demonstrated with standard nanospheres and protreins. An attempt to elucidate the capability of FI-AFlFFF system for the separation and size characterization of nanoparticles is made with a fumed silica particle sample. In FI-AFlFFF, field programming can be easily applied to improve separation speed and resolution for a highly retaining component (very large MW) by using flow circulation method. Programmed FI-AFlFFF separations are demonstrated with polystyrene sulfonate standards and pululans and the dynamic separation range of molecular weight is successfully expanded.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.457-463
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• 2009

The earthwork is essential procedure for all civil engineering projects. Because of its importance in terms of cost and time, it should be managed effectively. In light of this, The Intelligent Excavating System (IES) research consortium has established to improve the productivity, quality and safety of current excavating/earthwork system by the Ministry of Land, Transportation and Maritime Affairs (MLTM) of Korea. This paper summarizes ongoing research aimed at development knowledge and presents a framework of task planning and visualization system for IES. The task planning and visualization system consists of three functions. 1) Using digital terrain model which created by 3D laser scanner, the system can divide it and generates global/local work area so that the excavator can work through the area. 2) In order to operate and/or control the excavator, the system exports the location, paths of boom, arm and bucket data of the excavator to control center. 3) The task planning system is visualized on the computer programming aided-graphic interface which simulates the planned work processes and eventually assists the operator for the control of the excavator. The case study which we have performed, demonstrates the effectiveness of the proposed system.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.245-252
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• 2022

Risk identification for bridge projects is a knowledge-based and labor-intensive task involving several procedures and stakeholders. Presently, risk information of bridge projects is unstructured and stored in different sources and formats, hindering knowledge sharing, reuse, and automation of the risk identification process. Consequently, there is a need to develop structured and formalized risk information for bridge projects to aid effective risk identification and automation of the risk management processes to ensure project success. This study proposes a semantic risk breakdown structure (SRBS) to support risk identification for bridge projects. SRBS is a searchable hierarchical risk breakdown structure (RBS) developed with python programming language based on a semantic modeling approach. The proposed SRBS for risk identification of bridge projects consists of a 4-level tree structure with 11 categories of risks and 116 potential risks associated with bridge projects. The contributions of this paper are threefold. Firstly, this study fills the gap in knowledge by presenting a formalized risk breakdown structure that could enhance the risk identification of bridge projects. Secondly, the proposed SRBS can assist in the creation of a risk database to support the automation of the risk identification process for bridge projects to reduce manual efforts. Lastly, the proposed SRBS can be used as a risk ontology that could aid the development of an artificial intelligence-based integrated risk management system for construction projects.

• 한국건설관리학회논문집
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• 제24권4호
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• pp.60-73
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• 2023

The need for adopting automation technologies to improve inefficiencies in interior finishing modeling work is increasing during the Building Information Modeling (BIM) design stage. As a result, the use of visual programming languages (VPL) for practical applications is growing. However, undefined or incorrect space designations in BIM models can hinder the development of automated finishing modeling processes, resulting in erroneous corrections and rework. To address this challenge, this study first developed a rule-based automated interior finishing detailing module for floors, walls, and ceilings. In addition, an automated space integrity checking module with 86.69% ACC using the Multi-Layer Perceptron (MLP) model was developed. These modules were integrated into a design automation module for interior finishing, which was then verified for practical utility. The results showed that the automation module reduced the time required for modeling and integrity checking by 97.6% compared to manual work, confirming its utility in assisting BIM model development for interior finishing works.

• Journal of Electrical Engineering and information Science
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• 제1권2호
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• pp.1-8
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• 1996

This paper presents a text-driven discourse analysis system, called DPAS. DPAS constructs a discourse structure by weaving together clauses in the text by finding discourse relations between a clause and the clauses in a context. The basic processing model of DPAS is based on the stack based model of discourse analysis suggested by Grosz and Sidner. We extend the model with dynamic programming method to handle various discourse ambiguities effectively and efficiently. We develop the idea of a context space to keep all information of a context. DPAS parses a text by considering all possible discourse relations between a clause and a context. Since different discourse relations may result in different states of a context, DPAS maintains multiple context spaces for an ambiguous text. Since maintaining all interpretations until the whole text is processed requires too much computing resources, DPAS uses the idea of depth-limited search to limit the search space. If there is more than one discourse relation between an input clause and a context, DPAS constructs context spaces one context space for each discourse relation. Then, DPAS applies heuristics to choose the most desirable context space after it processes some more input clauses. Since the basic idea of DPAS is domain independent, although we used descriptive texts to demonstrate DPAS, we believe the idea of DPAS can be extended to understand other styles of texts.

• 한국수학교육학회지시리즈A:수학교육
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• 제63권2호
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• pp.233-254
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• 2024

This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.

• 한국산학기술학회논문지
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• 제16권4호
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• pp.2749-2756
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• 2015

최근 데이터의 질이 높아짐에 따라 영상을 처리하는데 많은 시간이 소모되는 문제가 제기되어 영상 처리 알고리즘의 가속화가 필요하게 됨으로써, 기존의 CPU와 CUDA(Compute Unified Device Architecture) 기반의 인식 시스템에서 연산속도와 성능이득 비교를 위해 OpenMP를 가지고 측정할 수 있는 문자 인식시스템으로 학습된 문자데이터가 입력되면 매칭이 가장 잘 되는 영상의 영역을 인식하는 환경으로 구현하여 각 영문 알파벳의 글씨체가 일정하고 크기가 규격화 되어 있으므로 문자를 학습하고 문자 정합도를 계산하기 위한 영상 매칭 방법을 구현하게 되었다. GPGPU(General Purpose GPU)프로그래밍 플랫폼 기술인 CUDA연산 기법을 이용하여 알고리즘을 빠르고 효율적으로 처리하는 OpenMP에서 인텔 i5 2500의 네 개의 코어를 사용하여 인식 할 때, 기존 CPU의 성능보다 4배의 속도가 나오지 않고 데이터의 분할과 병합 연산의 지연으로 인해 약 3.2배의 속도로 향상되는 가속화 방법을 제안하고 그래픽카드에서 처리하는 병렬처리 결과, 순차적 연산을 수행하였던 CPU 기반의 처리에 비해 성능이득이 약 21X(배)로 향상됨을 확인하였다.