• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.31-39
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• 2011

In this study, supervision resides fire mission against problems associated with case studies and surveys done through the side of the field work, technical personnel, fire management, including fire code aspects classified into three kinds of items dealt with the issue. Started at the scene of the problem in terms of performance, the issue of the construction process, mainly dealt with the issue at the time of completion. Fire management side, supervisor of technical personnel, human resources management issues, contract issues, fire code level, the frequent revisions of fire regulations, supervision, processing delays of the resulting report, the problem resides with the expansion of Fire Supervision target was mentioned. Finally, the target for each hierarchical supervision, and resident supervisor of the need for supervision of work performance test was carried out by the correlation.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.7-13
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• 1999

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input -output pair. First, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.785-787
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• 2005

In the Bluetooth specification version 1.0, one specific frequency in one piconet was created depending upon the device clock and the Bluetooth native address at one specific time slot in the frequency hopping method. The basic hopping pattern was arranging the 79 ISM frequency band in pseudo-random fashion. Possible problem is the chance of collision of ownership of one specific frequency by more than 2 wireless devices when they are within the communication-active range. In this paper, we propose the adaptive frequency hopping method in order to resolve the possible problem so that more than 2 wireless devices communicates with their own client devices without being interfered. The proposed method was implemented with HDL later to be synthesized with an automatic EDA synthesizer and verified as well. The implemented adaptive frequency hopping circuit operated normally at 24MHz which will be the target clock frequency of the target Bluetooth device.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.522-534
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• 2017

According to the characteristics of salvo attack for the multiple flight vehicles (MFV), the design of cooperative guidance law can be converted into the consensus problem of multi-vehicle system through the concept of multi-agent cooperative control. The flight vehicles can be divided into leader and followers depending on different functions, and the flight conditions of leader are independent of the ones of followers. The consensus problem of leader-follower multi-vehicle system is researched by graph theory, and the consensus protocol is also presented. Meanwhile, the finite time guidance law is designed for the flight vehicles via the finite time control method, and the system stability is also analyzed. Whereby, the guidance law can guarantee the line of sight (LOS) angular rates converge to zero in finite time, and hence the cooperative attack of the MFV can be realized. The effectiveness of the designed cooperative guidance method is validated through the simulation with a stationary target and a moving target, respectively.

• Journal of Power System Engineering
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• v.6 no.1
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.46-51
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• 2017

Recent controller design techniques often discretize the target system and implement a discrete controller that is digitized to match the target system. When constructing such a discrete system, it is necessary to first determine the sampling time. The smaller the sampling time is, the more advantageous it can be made similar to the original system, but the cost is a problem when realizing such a configuration as hardware. On the other hand, the longer the time, the more different the system is from the original system, and eventually the control becomes impossible. In this paper, we consider the above problem and propose a more logical approach to determine the sampling time in the discrete system and investigate the relation with the differential controller. We also apply this process to a nonlinear system called ARAGO disc and verify its validity through computer simulation.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.819-832
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• 2022

Cross-domain recommender system transfers knowledge across different domains to improve the recommendation performance in a target domain that has a relatively sparse model. However, they suffer from the "negative transfer" in which transferred knowledge operates as noise. This paper proposes a novel Multiple Fusion-based Deep Cross-Domain Recommendation named MFDCR. We exploit Doc2Vec, one of the famous word embedding techniques, to fuse data user-wise and transfer knowledge across multi-domains. It alleviates the "negative transfer" problem. Additionally, we introduce a simple multi-layer perception to learn the user-item interactions and predict the possibility of preferring items by users. Extensive experiments with three domain datasets from one of the most famous services Amazon demonstrate that MFDCR outperforms recent single and cross-domain recommendation algorithms. Furthermore, experimental results show that MFDCR can address the problem of "negative transfer" and improve recommendation performance for multiple domains simultaneously. In addition, we show that our approach is efficient in extending toward more domains.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.139-144
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• 2023

Engineers prefer deep neural networks (DNNs) for solving computer vision problems. However, DNNs pose two major problems. First, neural networks require large amounts of well-labeled data for training. Second, the covariate shift problem is common in computer vision problems. Domain adaptation has been proposed to mitigate this problem. Recent work on adversarial-learning-based unsupervised domain adaptation (UDA) has explained transferability and enabled the model to learn robust features. Despite this advantage, current methods do not guarantee the distinguishability of the latent space unless they consider class-aware information of the target domain. Furthermore, source and target examples alone cannot efficiently extract domain-invariant features from the encoded spaces. To alleviate the problems of existing UDA methods, we propose the mixup regularization in adversarial discriminative domain adaptation (ADDA) method. We validated the effectiveness and generality of the proposed method by performing experiments under three adaptation scenarios: MNIST to USPS, SVHN to MNIST, and MNIST to MNIST-M.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.211-216
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• 1996

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture o fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so 솜 t the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2001.11a
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• pp.61-66
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• 2001

In this research, the design parameters of embedded capacitors are extracted by modeling and fabrication. The traditional library of capactor has a few problems in applying the circuit. Its capacitance is discrete, so target values in any circuit often can't be obtained in library, To solve this problem, the characteristics of capacitors are detected in the variation with the shape and structure, and then the capacitors with the expected reactance value at target frequency are obtained, In this procedure, 3-dimensional structure simulation is performed to predict the characteiristics of capacitors.