• Title/Summary/Keyword: Weighted Average Model

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Development of ResNet-based WBC Classification Algorithm Using Super-pixel Image Segmentation

  • Lee, Kyu-Man;Kang, Soon-Ah
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.147-153
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    • 2018
  • In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

Dynamic RNN-CNN malware classifier correspond with Random Dimension Input Data (임의 차원 데이터 대응 Dynamic RNN-CNN 멀웨어 분류기)

  • Lim, Geun-Young;Cho, Young-Bok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.5
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    • pp.533-539
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    • 2019
  • This study proposes a malware classification model that can handle arbitrary length input data using the Microsoft Malware Classification Challenge dataset. We are based on imaging existing data from malware. The proposed model generates a lot of images when malware data is large, and generates a small image of small data. The generated image is learned as time series data by Dynamic RNN. The output value of the RNN is classified into malware by using only the highest weighted output by applying the Attention technique, and learning the RNN output value by Residual CNN again. Experiments on the proposed model showed a Micro-average F1 score of 92% in the validation data set. Experimental results show that the performance of a model capable of learning and classifying arbitrary length data can be verified without special feature extraction and dimension reduction.

Optimal Adjustment of Misestimated Control Model for a Process with Shift and White Noise (백색잡음과 Shift가 존재하는 공정에서 제어식이 부정확한 경우의 최적 보정)

  • Hwang, Ji-Bin;Kim, Ji-Hyun;Lee, Jae-Hyun;Kim, Sung-Shick
    • Journal of the Korea Society for Simulation
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    • v.16 no.4
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    • pp.43-55
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    • 2007
  • Moving average(MA) and exponentially weighted moving average(EWMA) are the two most popular control methods in manufacturing. Both methods are optimized under the assumption that the exact control equation is known. This paper focuses on the problems rising from estimation errors. Based on the accuracy of the estimated parameter and the range of the weight parameter $\lambda$, the limitations are identified and the performance of methods are evaluated. Optimal adjustment for process shift with misestimated control model and its application control methods to actual process is researched. The efficiency of proposed method is evaluated through simulation.

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Design of a Container Crane Controller Using the Fuzzy Control Technique (퍼지제어 기법을 이용한 컨테이너 크레인의 제어기 설계)

  • 소명옥;유희한;박재식;남택근;최재준;이병찬
    • Journal of Advanced Marine Engineering and Technology
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    • v.27 no.6
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    • pp.759-766
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    • 2003
  • The amount of container freight continuously has been increased. and the low efficiency of container crane causes jamming frequently in transportation and cargo handling at port. The conventional control techniques based on a mathematical model are not well suited for dealing with ill-defined and uncertain systems. Recently. Fuzzy control has been successfully applied to a wide variety of practical problems as robots. automatic train operation system. etc. In this paper. a fuzzy controller for container crane is proposed to accomplish a design of improved control system for minimizing the swing motion at destination. In this scheme a mathematical model for the system is obtained in state space form. Finally. to exhibit the tracking performance and robustness of the proposed controller. computer simulations were carried out with various references, parameter variations and disturbances.

A new damage index for seismic fragility analysis of reinforced concrete columns

  • Kang, Jun Won;Lee, Jeeho
    • Structural Engineering and Mechanics
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    • v.60 no.5
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    • pp.875-890
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    • 2016
  • A new structural damage index for seismic fragility analysis of reinforced concrete columns is developed based on a local tensile damage variable of the Lee and Fenves plastic-damage model. The proposed damage index is formulated from the nonlinear regression of experimental column test data. In contrast to the response-based damage index, the proposed damage index is well-defined in the form of a single monotonically-increasing function of the volume weighted average of local damage distribution, and provides the necessary computability and objectivity. It is shown that the present damage index can be appropriately zoned to be used in seismic fragility analysis. An application example in the computational seismic fragility evaluation of reinforced concrete columns validates the effectiveness of the proposed damage index.

A change point estimator in monitoring the parameters of a multivariate IMA(1, 1) model

  • Sohn, Sun-Yoel;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.525-533
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    • 2015
  • Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.

On the Study of Rationalization of Plant Layout - Orient ed Non-massing Jobbing Production Shop - (설비배치합리화에 관한 연구 - 다품종소량생산형태를 중심으로 -)

  • 조남호;이근희
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.7 no.10
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    • pp.1-16
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    • 1984
  • The purpose of this paper is to develop rational layout model for small and medium scale industry in Korea. The methodology of this paper is to light the importance of small and medium scale company. Moreover, to overcome the problem of layout in non-massing jobbing production shop this paper is proposed four techniques. So proposed layout model is obtained analytically in single, multiple facility location problem The result of this paper is as follows : First, alternatives to overcome abnormal layout in small and medium company are 1) GT (Group Technology) 2) SLP (Systematic Layout Planning) 3) OR (Operations Research) 4) Computer Second, in single facility location problem, Gradient method and square weighted average method are studied. Lastly in multiple facility location problem, heuristic method is obtained.

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Audio Source Separation Based on Residual Reprojection

  • Cho, Choongsang;Kim, Je Woo;Lee, Sangkeun
    • ETRI Journal
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    • v.37 no.4
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    • pp.780-786
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    • 2015
  • This paper describes an audio source separation that is based on nonnegative matrix factorization (NMF) and expectation maximization (EM). For stable and highperformance separation, an effective auxiliary source separation that extracts source residuals and reprojects them onto proper sources is proposed by taking into account an ambiguous region among sources and a source's refinement. Specifically, an additional NMF (model) is designed for the ambiguous region - whose elements are not easily represented by any existing or predefined NMFs of the sources. The residual signal can be extracted by inserting the aforementioned model into the NMF-EM-based audio separation. Then, it is refined by the weighted parameters of the separation and reprojected onto the separated sources. Experimental results demonstrate that the proposed scheme (outlined above) is more stable and outperforms existing algorithms by, on average, 4.4 dB in terms of the source distortion ratio.

ON MUTUAL AGREEMENT OF SUBJECTIVE RELIABILITY ANALYSIS RESULTS

  • Onisawa, Takehisa
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1406-1409
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    • 1993
  • This paper describes a model of the subjective reliability analysis, which uses a fuzzy set, natural language expressions and parameterized operations of fuzzy sets, and reflects analysts' subjectivity. The model has the problem of many different analysis results being obtained since the results depend on their subjectivity. As one of the solutions two kinds of mutual agreements based on the analysis results are considered. One is the intersection and the union of the fuzzy sets obtained by the analysis. The other is the weighted average of the fuzzy sets. This paper gives these interpretations from the viewpoint of system reliability analysis. This paper also shows examples of these considerations.

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A Case Study of the Habitat Changes for the Fish Community due to the Restoration of Pool-Riffle Sequence (여울-소 출현 복원을 통한 다양한 어종의 서식처 변화 연구)

  • Choi, Heung Sik;Choi, Jonggeun;Choi, Byungwoong
    • Ecology and Resilient Infrastructure
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    • v.7 no.1
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    • pp.53-62
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    • 2020
  • The present study aimed to investigate the impact of the restoration of the restoration technique on fish habitat using a physical habitat simulation in the Wonju-cheon Stream, Korea. The target species were Pungtungia herzi, Zacco platypus, and Zacco Koreanus, a dominant and sub-dominant species in the Wonju-cheon Stream. The River2D model was used for the computation of the flow and the habitat suitability index model was used to estimate the quality and quantity of habitat using habitat suitability curve. To assess the impact of pool-riffle sequence on change of fish habitat, this present study conducted using the each representative distance, namely, 50 m, 100 m, 200 m, and 300 m. Simulation results indicated that the pool-reffle sequence significantly increased the habitats for the target species than the result without considering pool-riffle sequence. On average, 53% of the Weighted Usable Area (WUA) increased due to pool-riffle sequence in the study area.