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모정훈,박순달 한국경영과학회 1995 經營 科學 Vol.12 No.2
The ordering method is used to reduce the fill-ins in interior point methods. In ordering, the data structure plays an important role. In this paper, first, we compare the efficiency and the memory storage requirement of the quotient graph structure and the clique storage. Next, we propose a method of reducing the number of cliques and a data structure for clique storage. Finally, we apply a method of merging rows and absorbing cliques and show the experimental results.
Jeonghoon Kwak,Kyon-Mo Yang,Ye Jun Lee,Min-Gyu Kim,Kap-Ho Seo 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.11
Deep learning models are used to track target-of-interest (ToI) objects with autonomous mobile robots (AMRs). A Siamese network based on few-shot learning is used when there is limited training data for the ToI objects. A Siamese network recognizes the object’s class based on the similarity between the input object and the template of the ToI object. The more similar the shape of the objects to be recognized, the smaller is the interclass variance of the features extracted from the object and the larger is the intra-class variance. If the inter-class variance is small and the intra-class variance is large, it is a different from the template object; however, since the calculated similarity can be high, it can be recognized as the same class object. Alternatively, it is an object of the same class as the template object, but can be recognized as a different class of object. To increase the inter-class variance and decrease the intra-class variance, a Siamese network training method is required. This paper proposes a method that recognizes ToI objects by increasing the difference in features between the ToI object and non-ToI objects when recognizing an object using a Siamese network. When distinguishing the ToI object from non-ToI objects, images that act as an anchor for each class are selected. The images inputted to the Siamese network are trained such that the corresponding class is close to the anchor of the selected class and far from other classes. The trained Siamese network then compares the anchor and similarity of each class to determine whether it is the ToI object. An experiment was conducted to analyze the training and execution results of the Siamese network using the proposed method. The recognition results using the proposed method and an existing template-based Siamese network were compared. The convolutional neural network model trained with the proposed method yielded an average accuracy of 93.95%. The proposed method could improve the performance by 23.68% compared to the existing template-based Siamese network.
Price of Simplicity under Congestion
Dongmyung Lee,Jeonghoon Mo,Guang Jin,Jinwoo Park IEEE 2012 IEEE journal on selected areas in communications Vol.30 No.11
<P>In this paper, we consider revenues of the NSP (network service provider) when there exists a 'congestion externality.' In particular, we compare revenues obtained using a flat price and two-part tariff and analyze the effect of congestion on the revenue loss when using a simple entry fee in lieu of the two-part tariff. Previous study has shown that when there is no delay disutility the revenue loss is small, which leads to a low 'Price of Simplicity.' However, in this study, we show that in an extreme case where all users are identical, the price of simplicity is substantial. Then we consider a more practical scenario where users have different preferences, and show that even in this case, under congestion externality, the price can be extremely high.</P>
Design and Analysis of a Cooperative Multichannel MAC Protocol for Heterogeneous Networks
Jiwoong Lee,Jeonghoon Mo,Tran Minh Trung,Walrand, Jean,So, Hoi-Sheung Wilson IEEE 2010 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY Vol.59 No.7
<P>Many incompatible wireless protocols proliferate in unlicensed bands, creating complex coexistence and connectivity problems. If the trend continues, such problems will continue to exist in future unlicensed bands. We take a different approach to spectrum sharing. Instead of proposing a distinct medium-access control (MAC) protocol for each type of application, we propose a family of parameterized MAC protocols called WiFlex, which can be tailored to different application needs, ranging from wireless sensors to media centers. However, these protocols allow communication and spectrum-sharing coordination among different types of devices. We envision this family to be based on a multichannel physical layer. The contributions of this paper include a novel asynchronous split phase (ASP) protocol with dynamic priority support, even in multiple-collision-domain environments. When links are bidirectional, WiFlex resolves the multichannel hidden-node problem, achieving collision-free data exchange in a multihop environment. ASP provides a mechanism for prioritization and fairness. The performance of the protocol is evaluated through analysis and simulation. The coexistence of heterogeneous devices and the support for different applications with high performance are demonstrated.</P>