• Title/Summary/Keyword: Improved Complex Method

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An Improved Method for the Determination of Scandium by Neutron Activation Analysis (스칸듐定量을 위한 改良된 放射化分析法)

  • Chung, Koo-Soon;Lee, Chul
    • Journal of the Korean Chemical Society
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    • v.8 no.2
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    • pp.88-91
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    • 1964
  • A rapid and simple method is described here for the determination of scandium in monazite by neutron activation analysis. The sample is irradiated for 20 hours at the neutron flux of $10^{12}$ thermal neutrons/$cm^2$/sec in the TRIGA MARK Ⅱ reactor, after which the sample is decomposed by fusion with concentrated sulfuric acid. The scandium-46 together with scandium carrier are separated from the irradiated sample by precipitating with ammonia, and are extracted by solvent extraction of the thiocyanate complex into ether. The induced radioactivity is measured by gamma scintillation spectrometry using the Multichannel Pulse Height Analyzer connected with 2"${\times}$2" NaI(Tl). The chemical yield is determined gravimetrically by precipitating scandium with mandelic acid. In order to check the efficiency of scandium separation and the errors from interfering activities of the other elements, scandium was separated by the cation exchange resin column, and the results from both samples were compared each other, which showed that the chemical procedure used in this work was as selective as the ion-exchange method with respect to scandium separation. The scandium contents in Korean monazite were found to be about 12 p. p. m.

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Work Allocation Methods and Performance Comparisons on the Virtual Parallel Computing System based on the IBM Aglets (IBM Aglets를 기반으로 하는 가상 병렬 컴퓨팅 시스템에서 작업 할당 기법과 성능 비교)

  • Kim, Kyong-Ha;Kim, Young-Hak;Oh, Gil-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.4
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    • pp.411-422
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    • 2002
  • Recently, there have been active researches about the VPCS (Virtual Parallel Computing System) based on multiple agents. The PVCS uses personal computers or workstations that are dispersed all over the internet, rather than a high-cost supercomputer, to solve complex problems that require a huge number of calculations. It can be made up with either homogeneous or heterogeneous computers, depending on resources available on the internet. In this paper, we propose a new method in order to distribute worker agents and work packages efficiently on the VPCS based on the IBM Aglets. The previous methods use mainly the master-slave pattern for distributing worker agents and work packages. However, in these methods the workload increases dramatically at the central master as the number of agents increases. As a solution to this problem, our method appoints worker agents to distribute worker agents and workload packages. The proposed method is evaluated in several ways on the VPCS, and its results are improved to be worthy of close attention as compared with the previous ones.

Fuzzy Modeling and Fuzzy Rule Generation in Global Approximate Response Surfaces (전역근사화 반응표면의 생성을 위한 퍼지모델링 및 퍼지규칙의 생성)

  • Lee, Jong-Soo;Hwang, Jeong-Su
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.3
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    • pp.231-238
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    • 2002
  • As a modeling method where the merits of fuzzy inference system and evolutionary computation are put together, evolutionary fuzzy modeling performs global approximate optimization. The paper proposes fuzzy clustering as fuzzy rule generation process which is one of the most important steps in evolutionary fuzzy modeling. With application of fuzzy clustering into the experiment or simulation results, fuzzy rules which properly describe non-linear and complex design problem can be obtained. The efficiency of evolutionary fuzzy modeling can be improved utilizing the membership degrees of data to clusters from the results of fuzzy clustering. To ensure the validity of the proposed method, the real design problem of an automotive inner trim is applied and the global approximation is achieved. Evolutionary fuzzy modeling is performed for several cases which differ in the number of clusters and the criterion of rule selection and their results are compared to prove that the proposed method can provide proper fuzzy rules for a given system and reduce computation time while maintaining the errors of modeling as a satisfactory level.

Graph Database based Malware Behavior Detection Techniques (그래프 데이터베이스 기반 악성코드 행위 탐지 기법)

  • Choi, Do-Hyeon;Park, Jung-Oh
    • Journal of Convergence for Information Technology
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    • v.11 no.4
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    • pp.55-63
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    • 2021
  • Recently, the incidence rate of malicious codes is over tens of thousands of cases, and it is known that it is almost impossible to detect/respond all of them. This study proposes a method for detecting multiple behavior patterns based on a graph database as a new method for dealing with malicious codes. Traditional dynamic analysis techniques and has applied a method to design and analyze graphs of representative associations malware pattern(process, PE, registry, etc.), another new graph model. As a result of the pattern verification, it was confirmed that the behavior of the basic malicious pattern was detected and the variant attack behavior(at least 5 steps), which was difficult to analyze in the past. In addition, as a result of the performance analysis, it was confirmed that the performance was improved by about 9.84 times or more compared to the relational database for complex patterns of 5 or more steps.

A Study on the Visualization Method for Figurative Art of Sculptures Using Metallic Materials - Based on the purpose of displaying in the residential complex (금속재료를 활용한 조형물의 비유적 이미지 시각화 방법 연구 - 주거 단지 전시를 목적으로)

  • Ko, Seung-Geun
    • Journal of the Korea Convergence Society
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    • v.12 no.1
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    • pp.225-230
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    • 2021
  • As the quality of our life has improved, residential complexes have become more diverse now. Modern residential complexes function as a place for meeting and communication between families and neighbors, including parks, lakes, and promenades, and exhibiting sculptures in residential spaces has become an important component. This study was conducted for the purpose of researching the design development method for the sculptures displayed in the residential space in accordance with these changes and demands of the era. Through the process of visualizing the figurative arts with metal and stone used as materials, the artist's thoughts and messages were put in the sculpture and the arts were completed as the shape of the sculpture that viewers could sympathize with. This design and formative research shows the possibility that various visual elements for sympathy with the creator's thoughts can be formed in a place with the specificity of living space by using a figurative visualization method. Therefore, further researches on figurative art of sculptures are required.

Linear interpolation and Machine Learning Methods for Gas Leakage Prediction Base on Multi-source Data Integration (다중소스 데이터 융합 기반의 가스 누출 예측을 위한 선형 보간 및 머신러닝 기법)

  • Dashdondov, Khongorzul;Jo, Kyuri;Kim, Mi-Hye
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.33-41
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    • 2022
  • In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

An Algorithm For Approximating The Performance of Multi-mode Network System Using Algebraic Property of System States (시스템 상태의 대수적 성질을 이용한 다중모드 네트워크 시스템 성능 근사계산 알고리즘)

  • Oh, Dae-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.127-137
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    • 2009
  • A practical algorithm of generating most probable states in decreasing order of probability of the network system state is suggested for approximating the performance of multi-mode network system using algebraic structure of the system states. Most complex system having network structure with multi-mode unit state is difficult to evaluate the performance or reliability due to exponentially increasing size of state space. Hence not an exact computing method but an approximated one is reasonable approach to solve the problem. To achieve the goal we should enumerate the network system states in order as a pre-processing step. In this paper, we suggest an improved algorithm of generating most probable multi-mode states to get the ordered system states efficiently. The method is compared with the previous algorithms in respective to memory requirement and empirical computing time. From the experiment proposed method has some advantages with regard to the criterion of algorithm performance. We investigate the advantages and disadvantage by illustrating experiment examples.

Sources separation of passive sonar array signal using recurrent neural network-based deep neural network with 3-D tensor (3-D 텐서와 recurrent neural network기반 심층신경망을 활용한 수동소나 다중 채널 신호분리 기술 개발)

  • Sangheon Lee;Dongku Jung;Jaesok Yu
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.4
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    • pp.357-363
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    • 2023
  • In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.

Efficient Structral Safety Monitoring of Large Structures Using Substructural Identification (부분구조추정법을 이용한 대형구조물의 효율적인 구조안전도 모니터링)

  • 윤정방;이형진
    • Journal of the Earthquake Engineering Society of Korea
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    • v.1 no.2
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    • pp.1-15
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    • 1997
  • This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

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A combined sewer design method using tractive force considering wastewater flow on non-rainy days and its application for improvement methods of sewer (청천시 오수량을 고려한 합류식 하수도 소류력 설계법과 이를 활용한 하수관거 개보수방안)

  • Ji, Hyon Wook;Yoo, Sung Soo;Song, Homyeon;Kang, Jeong-Hee
    • Journal of Korean Society of Water and Wastewater
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    • v.34 no.3
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    • pp.211-220
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    • 2020
  • When domestic sewage and rainwater runoff are discharged into a single sewer pipe, it is called a "combined sewer system." The sewage design standards in Korea specify the flow velocity based only on the volume of rainfall; therefore, sedimentation occurs on non-rainy days owing to the reduced flow rate and velocity. This sedimentation reduces the discharge capacity, causes unpleasant odors, and exacerbates the problem of combined sewer overflow concentration. To address this problem, the amount of sewage on non-rainy days, not just the volume of rainfall, should also be considered. There are various theories on sedimentation in sewer movement. This study introduces a self-cleansing velocity based on tractive force theory. By applying a self-cleansing velocity equivalent to the critical shear stress of a sand particle, sedimentation can be reduced on non-rainy days. The amount of sewage changes according to the water use pattern of citizens. The design hourly maximum wastewater flow was considered as a representative value, and the velocity of this flow should be more than the self-cleansing velocity. This design method requires a steeper gradient than existing design criteria. Therefore, the existing sewer pipelines need to be improved and repaired accordingly. In this study, five types of improvement and repair methods that can maximize the use of existing pipelines and minimize the depth of excavation are proposed. The key technologies utilized are trenchless sewer rehabilitation and complex cross-section pipes. Trenchless sewer rehabilitation is a popular sewage repair method. However, it is complex because the cross-section pipes do not have a universal design and require continuous research and development. In an old metropolis with a combined sewer system, it is difficult to carry out excavation work; hence, the methods presented in this study may be useful in the future.