• 로봇학회논문지
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• 제19권1호
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• pp.117-129
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• 2024

This paper introduces collective navigation through a narrow gap using a curriculum-based deep reinforcement learning algorithm for a swarm of unmanned aerial vehicles (UAVs). Collective navigation in complex environments is essential for various applications such as search and rescue, environment monitoring and military tasks operations. Conventional methods, which are easily interpretable from an engineering perspective, divide the navigation tasks into mapping, planning, and control; however, they struggle with increased latency and unmodeled environmental factors. Recently, learning-based methods have addressed these problems by employing the end-to-end framework with neural networks. Nonetheless, most existing learning-based approaches face challenges in complex scenarios particularly for navigating through a narrow gap or when a leader or informed UAV is unavailable. Our approach uses the information of a certain number of nearest neighboring UAVs and incorporates a task-specific curriculum to reduce learning time and train a robust model. The effectiveness of the proposed algorithm is verified through an ablation study and quantitative metrics. Simulation results demonstrate that our approach outperforms existing methods.

• 시스템엔지니어링학술지
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• 제17권2호
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• pp.69-81
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• 2021

The human performance issues and increased automation issues in advanced Small Modular Reactors (SMRs) are critical to numerous stakeholders in the nuclear industry, due to the undesirable implications targeting the Man Machine Interface Systems (MMIS) complexity of (Generation IV) SMRs. It is imperative that the design of future SMRs must address these problems. Nowadays, Multi Agent Systems (MAS) are used in the industrial sector to solve multiple complex problems; therefore incorporating this technology in the proposed innovative SMR (I-SMR) design will contribute greatly in the decision making process during plant operations, also reduce the number MCR operating crew and human errors. However, it is speculated that an increased level of complexity will be introduced. Prior to achieving the objectives of this research, the tools used to analyze the system for complexity reduction, are the McCabe's Cyclomatic complexity metric and the Henry-Kafura Information Flow metric. In this research, the systems engineering approach is used to guide the engineering process of complexity reduction concept of the system in its entirety.

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.866-878
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• 2021

Procedures play a key role in ensuring safe operation at nuclear power plants (NPPs). Development and maintenance of a large number of procedures reflecting the best knowledge available in all relevant areas is a complex job. This paper introduces a newly developed methodology and the implemented software, called iExtractor, for the extraction of syntactic and semantic information from NPP procedures utilizing natural language processing (NLP)-based technologies. The steps of the iExtractor integrated with sets of rules and an ontology for NPPs are described in detail with examples. Case study results of the iExtractor applied to selected procedures of a U.S. commercial NPP are also introduced. It is shown that the iExtractor can provide overall comprehension of the analyzed procedures and indicate parts of procedures that need improvement. The rich information extracted from procedures could be further utilized as a basis for their enhanced management.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1989년도 봄 학술발표회 논문집
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• pp.71-76
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• 1989

Structural design, generally engineering design, is a complex process combinding design knowledges and analysis techniques. While analysis techniques can be automated in an algorithmic fashion, relatively little work has been done in the area of the design automation. An effect approach method for the automation of the engineering design may be a hybrid system, in which design knowledges, specification requirements and interpretations are represented using an expert system methodology and numerically intensive operations of the design process are implemented using an algorithmic language such as FORTRAN. The purpose of this paper is concentrated on the knowledge of K-CLIPS(KAIST-C Language Integrated Production System) used to design and implement this hybrid system. In K-CLIPS, some representation methods : frame, production rule, fact and user defined function are used to construct the knowledge base. The hierarchical knowledges could be expressed more naturally with a little number of rules than other plain production systems.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 추계학술대회 논문집
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• pp.177-180
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• 2009

Tube hydroforming provides a number of advantages over the conventional stamping process, including fewer secondary operations, weight reduction, assembly simplification, adaptability to forming of complex structural components and improved structural strength and stiffness. A hydroformed vehicle body component has an attachment flange or the like-formed as an integral part of the hydroforming process. For a given flange shape, a parting plane for the dies is established relative to which the various surfaces of the flange shape, in cross section, have no significant reverse curvature. This study shows analysis results that form the flanged tubular parts in the hydroforming. The thickness variations and defects during the hydroforming for flange forming could be analyzed by FE analysis. FE analysis was performed by LS-DYNA/Dynaform 5.5.

• 전기학회논문지
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• 제63권7호
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• pp.1001-1007
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• 2014

This paper proposes a method to reduce operation time using discrete cosine transform and to improve image quality by the DC gain correction. Conventional filtered back projection (FBP) filtering in the frequency domain using Fourier transform, but the filtering process uses complex number operations. To simplify the filtering process, we propose a filtering process using discrete cosine transform. In addition, the image quality of reconstructed images are improved by correcting DC gain of sinograms. To correct the DC gain, we propose to find an optimum DC weight is defined as the ratio of sinogram DC and optimum DC. Experimental results show that the proposed method gets better performance than the conventional method for phantom and clinical CT images.

• 한국공작기계학회논문집
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• 제15권3호
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• pp.45-52
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• 2006

Burrs formed during face milling operations can be very difficult to characterize since there exist several parameters which have complex combined effects that affect the cutting process. Many researchers have attempted to predict burr characteristics including burr size and shape, using various experimental parameters such as cutting speed, feed rate, in-plane exit angle, and number of inserts. However, the results of these studies tend to be limited to a specific process parameter range and to certain materials. In this paper, the Taguchi method, a systematic optimization method for design and analysis of experiments, is introduced to acquire optimum cutting conditions for burr minimization. In addition, an in process monitoring scheme using an artificial neural network is presented for the prediction of burr types.

• 경영과학
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• 제34권2호
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• pp.57-66
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• 2017

The purpose of this study is to analyze the multidimensional productivity of the shipbuilding performance and to explain the role of different factors, such as man-hour, dock period, number of building block, launching process rate, automatic welding percent, and drawing fault rate which are important production-related variables in most shipbuilding companies. The shipbuilding productivity is obtained using Data Envelopment Analysis (DEA) approach. Then, a Tobit model is considered to measure the influence of different factors on the measured productivity. The results reveal that this productivity measure can substitute a representative shipbuilding productivity index (CGT/man-hour) in shipbuilding industries. Also, this multidimensional productivity analysis using DEA and Tobit reveals complex relationships between production-related variables and CGT and sale.

• 한국정밀공학회지
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• 제18권12호
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• pp.130-136
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• 2001

Burrs formed during face milling operations are very hard to characterize because there are many parameters that affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complex combined effects between the parameters. In this paper, the Taguchi method, which is a systematic optimization application in design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization in face milling. Also, analysis of variance (AVOVA) is employed to study the performance characteristics in more detail. Experimental verifications are provided to show the effectiveness of this approach.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1089-1092
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• 1998

Conventional floating-point adders have one data-path that is used for all operations. This paper describes a floatingpoint adder eeveloped for low power consumption, which has three data-paths one of which is selected according to the exponent difference. The first is applied to the case that the absolute exponent difference (AED) of two operands is less than 1, and the second is for 1