• Title/Summary/Keyword: mean number of objects

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Estimating the mean number of objects in M/H2/1 model for web service

  • Lee, Yongjin
    • International journal of advanced smart convergence
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    • v.11 no.3
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    • pp.1-6
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    • 2022
  • In this paper, we estimate the mean number of objects in the M/H2/1 model for web service when the mean object size in the M/H2/1 model is equal to that of the M/G/1/PS and M/BP/1 models. To this end, we use the mean object size obtained by assuming that the mean latency of deterministic model is equal to that of M/H2/1, M/G/1/PS, and M/BP/1 models, respectively. Computational experiments show that if the shape parameter of the M/BP/1 model is 1.1 and the system load is greater than 0.35, the mean number of objects in the M/H2/1 model when mean object size of M/H2/1 model is the same as that of M/G/1/PS model is almost equal to the mean number of objects in the M/H2/1 model when the mean object size of M/H2/1 model is the same as that of M/BP/1 model. In addition, as the upper limit of the M/BP/1 model increases, the number of objects in the M/H2/1 model converges to one, which increases latency. These results mean that it is efficient to use small-sized objects in the web service environment.

Relationship between inclusion level of Vachellia tortilis leaf meal and behavioral activities of finishing pigs

  • Thabethe, Fortune;Khanyile, Mbongeni;Ncobela, Cyprial Ndumiso;Chimonyo, Michael
    • Asian-Australasian Journal of Animal Sciences
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    • v.33 no.1
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    • pp.177-185
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    • 2020
  • Objective: The study was conducted to establish a relationship between inclusion level of Vachellia tortilis (V. tortilis) leaf meal and time spent on different behavioral activities by finishing pigs. Methods: A total of forty-eight male Large White×Landrace finishing pigs with a mean (±standard deviation) body weight of 63.8±3.28 kg aged 14 wks were assigned to individual pens in a completely randomized design. Pigs were fed on diets containing 0, 30, 60, 90, 120, and 150 g/kg dry matter of V. tortilis leaf meal ad libitum with fresh water provided throughout the trial. There were eight pigs in each experimental diet. The behavior of pigs was observed for three wks twice a wk from 0600 to 1800 h using six closed circuit television cameras. Results: Increasing levels of V. tortilis leaf meal caused a linear decrease (p<0.05) in time spent eating, lying down and the number of visit to the feeder. Time spent standing and biting objects increased linearly (p<0.05) with increasing inclusion level of V. tortilis leaf meal. The was a negative linear relationship (p<0.05) between condensed tannins versus time spent eating, lying down and number of feeder visits. Condensed tannins showed a positive linear relationship (p<0.05) with time spent standing and biting objects. Neutral detergent fiber caused a linear decrease (p<0.05) in number of feeder visits, time spent eating, time spent standing. Conclusion: Inclusion level of V. tortilis leaf meal reduces time spent eating, lying down and the number of feeder visit while prolonging time spent standing and biting of objects. Condensed tannins and dietary fiber are among nutritional factors affecting behavioral activities displayed by finishing pigs.

A Study of an Extended Fuzzy Cluster Analysis on Special Shape Data (특별한 형태의 자료에 대한 확장된 Fuzzy 집락분석방법에 관한 연구)

  • 임대혁
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.25 no.6
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    • pp.36-41
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    • 2002
  • We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. we show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

A Study of Simulation Method and New Fuzzy Cluster Analysis (새로운 Fuzzy 집락분석방법과 Simulation기법에 관한 연구)

  • Im Dae-Heug
    • Management & Information Systems Review
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    • v.14
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    • pp.51-65
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    • 2004
  • We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we Propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. We show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

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A Study on an Extended Fuzzy Cluster Analysis (확장된 Fuzzy 집락분석방법에 관한 연구)

  • Im Dae-Heug
    • Management & Information Systems Review
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    • v.9
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    • pp.25-39
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    • 2002
  • We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the. ISODATA used traditionally in this field since the objective function is changed. We show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

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System Development of Precision Vision Measurement Using Fuzzy C-means and Possibilistic C-Means Algorithm (Fuzzy C-means와 확률 C-Means를 결합한 정밀 영상측정 시스템 개발)

  • 김석현
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1999.12a
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    • pp.315-323
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    • 1999
  • The measuring systems of auto-parts are most of greater part very expensive. This paper tries to study to make a low-cost measuring equipment. There's several kinds of parts in automobile. In this study, we take aircon-switch called magnet coil-housing as the object of measurements. The measurements of this product is currently in difficult situations at factory. In the case of the mesuring objects being big sizes and camera sensor having under 410000 pixels, the key point is the number of pixels not to be changed whenever the same object is measured under the same position. We modified and used fuzzy c-means algorithm to get mostly without the change of the numbers of pixels exactly. Also, the standardized ruler is necessary to measure the length of the object but it is not easy to get the precised ruler. Therefore, the standard length has been taken as the mean value of the pixels in the previous passed objects manually obtained at factory. The results are displayed on monitor and transferred these signals to the microprocessor through RSC-232 port to determine a good or bad of products.

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Visual Object Tracking Fusing CNN and Color Histogram based Tracker and Depth Estimation for Automatic Immersive Audio Mixing

  • Park, Sung-Jun;Islam, Md. Mahbubul;Baek, Joong-Hwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.1121-1141
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    • 2020
  • We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

Performance Improvement of Motion Compensation using Motion Vector Segmentation (움직임 벡터 분할을 이용한 움직임 보상 성능 개선)

  • 채종길;곽성일;황찬식
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.3
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    • pp.77-88
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    • 1995
  • It is assumed in the block matching algorithm(BMA) that all the pels in a block have a same motion vector. Then, the motion vector of a block in the BMA is matched to only one or none of the objects in the worst case if objects in a block have different motion vectors. This is apparent in the motion estimation using the fast BMA which has the effect of reducing the computation time and hardware complexity, compared to the full search BMA. Although the motion vector in the motion estimation using small block size is accurate, the increased number of bits is required to represent motion vectors. In this paper, new motion vector segmentation with less additional information and hardware complexity than the conventional method is proposed. In the proposed method, a motion vector is derived from the block for motion vector segmentation and another motion vector is extracted from four neighboring blocks to consiture a motion vector pair. For the accurate motion vector of each subblock, the motion vector is assigned to each subblock by mean squared error measure. And the overlapped motion compensation using window is also applied to reduce displaced frame difference.

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System Development of Precision Vision Measurement Using Fuzzy C-Means Algorithm (Fuzzy C-Means를 이용한 정밀 영상측정 시스템 개발)

  • 김석현
    • Journal of Korea Society of Industrial Information Systems
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    • v.4 no.4
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    • pp.7-14
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    • 1999
  • The measuring systems of auto-parts are most of greater part very expensive. This paper tries to study to make a low-cost measuring equipment there's several kinds of parts in automobile. In this study, we take aircon-switch called magnet coil-housing as the object of measurements. The measurements of this product is currently in difficult situations at factory. In the case of the mesuring objects being big sizes and camera sensor having under 410000 pixels, the key point is the number of pixels not to be changed whenever the same object is measured under the same position. We modified and used fuzzy c-means algorithm to get mostly without the change of the numbers of pixels exactly. Also, the standardized ruler is necessary to measure the length of the object but it is not easy to get the precised ruler. Therefore, the standard length has been taken as the mean value of the pixels in the previous passed objects manually obtained at factory. The results are displayed on monitor and transferred these signals to the microprocessor through RSC-232 port to determine a good or bad of products.

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A Study on the Home Health Care Need of Postpartum Mothers (산욕기 산모의 가정간호 요구도 조사)

  • Yang, Young-Ok;Choi, So-Young
    • Journal of Home Health Care Nursing
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    • v.10 no.2
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    • pp.148-157
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    • 2003
  • The purpose of this study was to provide the basic data for developing a program for effective intervention for home health care need of postpartum mothers and newborn babies. The subjects were 104 women. The data were collected from march, 2003 to June, using a 81 item questionnaire and analyzed by SPSS program for frequency, Mean, ANOVA. The results were as follow. 1. The mean of care needs of newborn babies was higher than that of physical demand of Postpartum mothers. The mean of physical demand of Postpartum mothers was $3.99\pm.42$. The mean of care needs of newborn babies was $4.11\pm.50$. 2. The most highest mean of physical demand of Postpartum mothers was wound care for caesarean section and episiotomy($4.53\pm.66$), and then breast engorgement care($4.38\pm.71$). The most highest mean of care needs of newborn babies was emergency care methods($4.58\pm.52$), and then infection control $4.51\pm.56$). 3. 66.3% of postpartum mothers positively desired consultation hospitals centered home care need during postpartial periods. 4. Influential variables of home health care need was postpartial periods. they wanted the first week after delivery, more freqently visiting of home care nurse. 37.5% of postpatial mothers wanted visiting within 1 weeks after delivery. 31.7% wanted 2 times/week. In conclusion, it is necessary to study to make a program in nursing of home health care for postpartum mothers, and to keep on studying repeatedly in order to raise the number of objects and to find related variables.

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