• Journal of Biosystems Engineering
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• 제37권4호
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• 대한전자공학회논문지TC
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• 제43권4호
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• pp.58-66
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• 2006

본 논문에서는 설계자가 원하는 주파수 특성을 갖는 FSS(Frequency Selective Surface)를 자동으로 설계해주는 시스템을 개발하고 실제 적용한 예를 기술한다. 설계 시스템은 전자파 산란 해석이론, 실제 제작한 FSS들의 특성을 측정하여 구축된 DB, 그리고 유전 알고리즘을 이용해서 설계자가 기대하는 특성을 가진 FSS의 설계 요소들을 제시한다. 설계 시스템은 첫 단계로 설계자가 요구한 특성과 가장 유사한 특성을 갖는 FSS 파라미터들을 DB로부터 구하고, 두 번째 단계로 이 파라미터들로부터 초기 개체들을 구성하여 유전학적 진화를 통해 설계자가 요구한 특성을 갖는 FSS 설계 파라미터가 출력되도록 개발되었다. 유전 알고리즘 내에서 사용되는 FSS 해석이론은 실제 제작된 FSS 샘플을 혼 안테나를 사용하여 실제로 측정한 데이터와 비교 분석하여 그 타당성을 검증하였다. 아울러 FSS를 제작하는 과정도 간단히 소개하였다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권4호
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• pp.291-302
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• 2013

NAND flash memory (NFM) based storage devices, e.g. Solid State Drive (SSD), are rapidly replacing conventional storage devices, e.g. Hard Disk Drive (HDD). As NAND flash memory technology advances, its specification has evolved to support denser cells and larger pages and blocks. However, efforts to fully understand their impacts on design objectives such as performance, power, and cost for various applications are often neglected. Our research shows this recent trend can adversely affect the design objectives depending on the characteristics of applications. Past works mostly focused on improving the specific design objectives of NFM based systems via various architectural solutions when the specification of NFM is given. Several other works attempted to model and characterize NFM but did not access the system-level impacts of individual parameters. To the best of our knowledge, this paper is the first work that considers the specification of NFM as the design parameters of NAND flash storage devices (NFSDs) and analyzes the characteristics of various synthesized and real traces and their interaction with design parameters. Our research shows that optimizing design parameters depends heavily on the characteristics of applications. The main contribution of this research is to understand the effects of low-level specifications of NFM, e.g. cell type, page size, and block size, on system-level metrics such as performance, cost, and power consumption in various applications with different characteristics, e.g. request length, update ratios, read-and-modify ratios. Experimental results show that the optimized page and block size can achieve up to 15 times better performance than the conventional NFM configuration in various applications. The results can be used to optimize the system-level objectives of a system with specific applications, e.g. embedded systems with NFM chips, or predict the future direction of NFM.

• Computers and Concrete
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• 제33권5호
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

• Fibers and Polymers
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• 제7권4호
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• pp.344-351
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• 2006

This paper is intended to determine the optimal processing parameters applied to the dyeing procedure so that the desired color strength of a raw fabric can be achieved. Moreover, the processing parameters are also used for constructing a system to predict the fabric quality. The fabric selected is the nylon and Lycra blend. The dyestuff used for dyeing is acid dyestuff and the dyeing method is one-bath-two-section. The Taguchi quality method is applied for parameter design. The analysis of variance (ANOVA) is applied to arrange the optimal condition, significant factors and the percentage contributions. In the experiment, according to the target value, a confirmation experiment is conducted to evaluate the reliability. Furthermore, the genetic algorithm (GA) is combined with the back propagation neural network (BPNN) in order to establish the forecasting system for searching the best connecting weights of BPNN. It can be shown that this combination not only enhances the efficiency of the learning algorithm, but also decreases the dependency of the initial condition during the network training. Most of all, the robustness of the learning algorithm will be increased and the quality characteristic of fabric will be precisely predicted.

• ETRI Journal
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• 제36권5호
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• pp.704-713
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• 2014

Most natural language processing tasks depend on the outputs of some other tasks. Thus, they involve other tasks as subtasks. The main problem of this type of pipelined model is that the optimality of the subtasks that are trained with their own data is not guaranteed in the final target task, since the subtasks are not optimized with respect to the target task. As a solution to this problem, this paper proposes a consolidation of subtasks for a target task ($CST^2$). In $CST^2$, all parameters of a target task and its subtasks are optimized to fulfill the objective of the target task. $CST^2$ finds such optimized parameters through a backpropagation algorithm. In experiments in which text chunking is a target task and part-of-speech tagging is its subtask, $CST^2$ outperforms a traditional pipelined text chunker. The experimental results prove the effectiveness of optimizing subtasks with respect to the target task.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제43회 하계 정기 학술대회 초록집
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• pp.274-274
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• 2012

We have researched on controlling an electron temperature and a plasma collision frequency to study the effect of collisions on helicon plasmas. So, we have designed and constructed an electron cyclotron resonance (ECR) heating system in the helicon device as an auxiliary heating source. Since then, we have tried to optimize experimental designs such as a magnetic field configuration for ECR heating and 2.45GHz microwave launching system for its power transfer to the plasma effectively, and have characterized plasma parameters using a Langmuir probe. For improving an efficiency of the ECR heating with R-wave in the helicon plasma, we would understand an effect of R-wave propagation with ECR heating in the helicon plasma, because the efficiency of ECR heating with R-wave depends on some factors such as electron temperature, electron density, and magnetic field gradient. Firstly, we calculate the effect of R-wave propagation into the ECR zone in the plasma with those factors. We modify the magnetic field configuration and this system for the effective ECR heating in the plasma. Finally, after optimizing this system, the plasma parameters such as electron temperature and electron density are characterized by a RF compensated Langmuir probe.

• Korean Chemical Engineering Research
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• 제55권5호
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• pp.652-659
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• 2017

In the present research, in order to predict activity coefficient of inorganic ions in electrolyte solution of a petroleum system, we studied 13 components in the electrolyte solution, including $H_2O$, $CO_2$ (aq), $H^+$, $Na^+$, $Ba^{2+}$, $Ca^{2+}$, $Sr^{2+}$, $Mg^{2+}$, $SO_4$, $CO_3$, $OH^-$, $Cl^-$, and $HCO_3$. To predict the activity coefficient of the components of the petroleum system (a solid/liquid equilibrium system), activity coefficient model of Extended UNIQUAC was studied, along with its adjustable parameters optimized based on a genetic algorithm. The total calculated error associated with optimizing the adjustable parameters of Extended UNIQUAC model considering the 13 components under study at three temperature levels (298.15, 323.15, and 373.15 K) using the genetic algorithm is found to be 0.07.

• 한국재료학회지
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• 제11권11호
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• pp.965-971
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• 2001

The objective of this study is to investigate the characteristics - microstructure, hardness, adhesive strength and friction coefficient - of the coatings with aging - treatment after optimizing internal- plasma spraying parameters for Al-30wt%Si powder as a basic research to manufacture the cylinder block bore for Al engine composed of Al-30wt%Si alloy on Al alloy, The optimum internal-plasma spraying parameters of Al-30wt%Si alloy are summarized as follows: voltage: 37.5V, current: 160A, working distance: 25mm, gun traverse speed: 4.5mm/s, rotating speed: 518m/min. The primary Si particles grew aggressively with increasing heat-treating temperature. The hardness of the as-sprayed coating was about Hv=275 but this value was abruptly decreased with increasing heat-treating temperature. And average friction coefficient of the coating was below 0.08 after heat treatment for 48h at $175^{\circ}C$.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1632-1644
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• 2007

Wireless Mesh Networks aim to attain large connectivity with minimum performance degradation, as network size is increase. As such, scalability is one of the main characteristics of Wireless Mesh Networks that differentiates it from other wireless networks. This characteristic creates the need for bandwidth efficiency strategies to ensure that network performance does not degrade as the size of the network increase. Several researches have been done to realize mesh networks. However, the researches conducted were mostly focused on a per TCP/IP layer basis. Also, the studies on bandwidth efficiency and bandwidth improvement are usually dealt with as separate issues. This paper aims to simultaneously study bandwidth efficiency and improvement. Aside from optimizing the bandwidth given a fixed capacity, the capacity is also increased using results of physical layer studies. In this paper, the capacity is improved by using the concept of non-overlapping channels for wireless communication. A channel allocation scheme is conceptualized to choose the transmission channel that would optimize the network performance parameters with consideration of chosen Quality of Service (QoS) parameters. Network utility maximization is used to optimize the bandwidth after channel selection. Furthermore, a routing scheme is proposed using the results of the network utilization method and the channel allocation scheme to find the optimal path that would maximize the network gain.