• Title/Summary/Keyword: Spectrum of a graph

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Quantum Bacterial Foraging Optimization for Cognitive Radio Spectrum Allocation

  • Li, Fei;Wu, Jiulong;Ge, Wenxue;Ji, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.2
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    • pp.564-582
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    • 2015
  • This paper proposes a novel swarm intelligence optimization method which integrates bacterial foraging optimization (BFO) with quantum computing, called quantum bacterial foraging optimization (QBFO) algorithm. In QBFO, a multi-qubit which can represent a linear superposition of states in search space probabilistically is used to represent a bacterium, so that the quantum bacteria representation has a better characteristic of population diversity. A quantum rotation gate is designed to simulate the chemotactic step for the sake of driving the bacteria toward better solutions. Several tests are conducted based on benchmark functions including multi-peak function to evaluate optimization performance of the proposed algorithm. Numerical results show that the proposed QBFO has more powerful properties in terms of convergence rate, stability and the ability of searching for the global optimal solution than the original BFO and quantum genetic algorithm. Furthermore, we examine the employment of our proposed QBFO for cognitive radio spectrum allocation. The results indicate that the proposed QBFO based spectrum allocation scheme achieves high efficiency of spectrum usage and improves the transmission performance of secondary users, as compared to color sensitive graph coloring algorithm and quantum genetic algorithm.

A Validation Study of the CARS-2 Compared With the ADOS-2 in the Diagnosis of Autism Spectrum Disorder: A Suggestion for Cutoff Scores

  • Seong-In Ji;Hyungseo Park;Sun Ah Yoon;Soon-Beom Hong
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.34 no.1
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    • pp.40-50
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    • 2023
  • Objectives: This study examined the validity of the Childhood Autism Rating Scale, Second Edition (CARS-2) compared with the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) in identifying autism spectrum disorder (ASD). Methods: A total of 237 children were tested using both the CARS-2 and ADOS-2. We examined the correlation using Pearson's correlation analysis. In addition, we used a receiver operating characteristic graph to determine the optimal standard version of the CARS-2 (CARS2-ST) cutoff score for ASD diagnosis using the ADOS-2. Results: The concurrent validity of the CARS2-ST was demonstrated by a significant correlation with the ADOS-2 (r=0.864, p<0.001). The optimal CARS2-ST cutoff scores were 30 and 28.5 for identifying autism and autism spectrum, respectively, based on the ADOS-2. Conclusion: We suggest a newly derived CARS2-ST cutoff score of 28.5 for screening ASD and providing early intervention.

A Multi-Layer Graphical Model for Constrained Spectral Segmentation

  • Kim, Tae Hoon;Lee, Kyoung Mu;Lee, Sang Uk
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.07a
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    • pp.437-438
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    • 2011
  • Spectral segmentation is a major trend in image segmentation. Specially, constrained spectral segmentation, inspired by the user-given inputs, remains its challenging task. Since it makes use of the spectrum of the affinity matrix of a given image, its overall quality depends mainly on how to design the graphical model. In this work, we propose a sparse, multi-layer graphical model, where the pixels and the over-segmented regions are the graph nodes. Here, the graph affinities are computed by using the must-link and cannot-link constraints as well as the likelihoods that each node has a specific label. They are then used to simultaneously cluster all pixels and regions into visually coherent groups across all layers in a single multi-layer framework of Normalized Cuts. Although we incorporate only the adjacent connections in the multi-layer graph, the foreground object can be efficiently extracted in the spectral framework. The experimental results demonstrate the relevance of our algorithm as compared to existing popular algorithms.

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DARK ENERGY REFLECTIONS IN THE REDSHIFT-SPACE QUADRUPOLE

  • NISHIOKA HIROAKI;YAMAMOTO KAZUHIRO;BASSETT BRUCE A.
    • Journal of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.175-178
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    • 2005
  • We show that next-generation galaxy surveys such as KAOS (the Kilo-Aperture Optical Spectro-graph)will constrain dark energy even if the baryon oscillations are missing from the monopole power spectrum and the bias is scale- and time-dependent KAOS will accurately measure the quadrupole power spectrum which gives the leading anisotropies in the power spectrum in redshift space due to peculiar velocities, the finger of God effect, as well as the Alcock-Paczynski effect. The combination of monopole and quadrupole power spectra powerfully breaks the degeneracy between the bias parameters and dark energy and, in the complete absence of baryon oscillations ($\Omega$b = 0), leads to a roughly $500\%$ improvement in constraints on dark energy compared with the monopole spectrum alone. As a result, for KAOS the worst case with no oscillations has dark energy errors only mildly degraded relative to the ideal case, providing insurance on the robustness of KAOS constraints on dark energy. We show that nonlinear effects are crucial in correctly evaluating the quadrupole and significantly improving the constraints on dark energy when we allow for multi-parameter scale-dependent bias.

Traffic Speed Prediction Based on Graph Neural Networks for Intelligent Transportation System (지능형 교통 시스템을 위한 Graph Neural Networks 기반 교통 속도 예측)

  • Kim, Sunghoon;Park, Jonghyuk;Choi, Yerim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.1
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    • pp.70-85
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    • 2021
  • Deep learning methodology, which has been actively studied in recent years, has improved the performance of artificial intelligence. Accordingly, systems utilizing deep learning have been proposed in various industries. In traffic systems, spatio-temporal graph modeling using GNN was found to be effective in predicting traffic speed. Still, it has a disadvantage that the model is trained inefficiently due to the memory bottleneck. Therefore, in this study, the road network is clustered through the graph clustering algorithm to reduce memory bottlenecks and simultaneously achieve superior performance. In order to verify the proposed method, the similarity of road speed distribution was measured using Jensen-Shannon divergence based on the analysis result of Incheon UTIC data. Then, the road network was clustered by spectrum clustering based on the measured similarity. As a result of the experiments, it was found that when the road network was divided into seven networks, the memory bottleneck was alleviated while recording the best performance compared to the baselines with MAE of 5.52km/h.

Multipath Routing and Spectrum Allocation for Network Coding Enabled Elastic Optical Networks

  • Wang, Xin;Gu, Rentao;Ji, Yuefeng
    • Current Optics and Photonics
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    • v.1 no.5
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    • pp.456-467
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    • 2017
  • The benefits of network coding in all-optical multicast networks have been widely demonstrated. In this paper, we mainly discuss the multicast service efficiently provisioning problem in the network coding enabled elastic optical networks (EONs). Although most research on routing and spectrum allocation (RSA) has been widely studied in the elastic optical networks (EONs), rare research studies RSA for multicast in the network coding enabled EON, especially considering the time delay constraint. We propose an efficient heuristic algorithm, called Network Coding based Multicast Capable-Multipath Routing and Spectrum Allocation (NCMC-MRSA) to solve the multipath RSA for multicast services in the network coding enabled EON. The well-known layered graph approach is utilized for NCMC-MRSA, and two request ordering strategies are utilized for multiple multicast requests. From the simulation results, we observe that the proposed algorithm NCMC-MRSA performs more efficient spectrum utilization compared with the benchmark algorithms. NCMC-MRSA utilizing the spectrum request balancing (SRB) ordering strategy shows the most efficient spectrum utilization performance among other algorithms in most test networks. Note that we also observe that the efficiency of NCMC-MRSA shows more obvious than the benchmark algorithm in large networks. We also conduct the performance comparisons of two request ordering strategies for NCMC-MRSA. Besides, we also evaluate the impact of the number of the linkdisjoint parallel w paths on the spectrum utilization performance of the proposed algorithm NCMC-MRSA. It is interesting to find that the change of the parameter w in a certain range has a significant impact on the performance of NCMC-MRSA. As the parameter w increases to a certain value, the performances of NCMC-MRSA cannot be affected by the change of w any more.

Pattern Classification of the QRS-complexes Using Relational Correlation (관계상관식을 이용한 QRS 패턴분류)

  • Hwang, Seon-Cheol;Jeong, Hee-Kyo;Shin, Kun-Soo;Lee, Byung-Chae;Lee, Myoung-Ho
    • Proceedings of the KIEE Conference
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    • 1990.11a
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    • pp.428-431
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    • 1990
  • This paper describes a pattern classification algorithm of QRS-complexes using significant point detection for extracting features of signals. Significant point extraction was processed by zero-crossing method, and decision function based on relational spectrum was used for pattern classification of the QRS-complexes. The hierarchical AND/OR graph was obtained by decomposing the signal, and by use of this graph, QRS's patterns were classified. By using the proposed algorithm, the accuracy of pattern classification and the processing speed were improved.

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A Study of Synchronization in Spread Spectrum System (스펙트럼 확산 시스템에서 동기에 관한 연구)

  • 강성봉;김원후
    • Proceedings of the Korean Institute of Communication Sciences Conference
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    • 1984.10a
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    • pp.43-47
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    • 1984
  • This paper describes the mean time delay and its variance before transition from search to lock mode by means of signal flow graph and its transfer function. A relation between hit probability and search stage number is presented with the comparison of the open loop and closed loop. From these results optimum transition probability which we must hold can be obtained.

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SOME RESULTS ON STARLIKE TREES AND SUNLIKE GRAPHS

  • Mirko, Lepovic
    • Journal of applied mathematics & informatics
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    • v.11 no.1_2
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    • pp.109-123
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    • 2003
  • A tree is called starlike if it has exactly one vertex of degree greate. than two. In [4] it was proved that two starlike trees G and H are cospectral if and only if they are isomorphic. We prove here that there exist no two non-isomorphic Laplacian cospectral starlike trees. Further, let G be a simple graph of order n with vertex set V(G) : {1,2, …, n} and let H = {$H_1$, $H_2$, …, $H_{n}$} be a family of rooted graphs. According to [2], the rooted product G(H) is the graph obtained by identifying the root of $H_{i}$ with the i-th vertex of G. In particular, if H is the family of the paths $P_k_1,P_k_2,...P_k_2$ with the rooted vertices of degree one, in this paper the corresponding graph G(H) is called the sunlike graph and is denoted by G($k_1,k_2,...k_n$). For any $(x_1,x_2,...,x_n)\;\in\;{I_*}^n$, where $I_{*}$ = : {0,1}, let G$(x_1,x_2,...,x_n)$ be the subgraph of G which is obtained by deleting the vertices $i_1,i_2,...i_j\;\in\;V(G)\;(O\leq j\leq n)$, provided that $x_i_1=x_i_2=...=x_i_j=o.\;Let \;G[x_1,x_2,...x_n]$ be characteristic polynomial of G$(x_1,x_2,...,x_n)$, understanding that G[0,0,...,0] $\equiv$1. We prove that $G[k_1,k_2,...,k_n]-\sum_{x\in In}[{\prod_{\imath=1}}^n\;P_k_i+x_i-2(\lambda)](-1)...G[x_1,x_2,...,X_n]$ where x=($x_1,x_2,...,x_n$);G[$k_1,k_2,...,k_n$] and $P_n(\lambda)$ denote the characteristic polynomial of G($k_1,k_2,...,k_n$) and $P_n$, respectively. Besides, if G is a graph with $\lambda_1(G)\;\geq1$ we show that $\lambda_1(G)\;\leq\;\lambda_1(G(k_1,k_2,...,k_n))<\lambda_1(G)_{\lambda_1}^{-1}(G}$ for all positive integers $k_1,k_2,...,k_n$, where $\lambda_1$ denotes the largest eigenvalue.

Self-organized Spectrum Access in Small-cell Networks with Dynamic Loads

  • Wu, Ducheng;Wu, Qihui;Xu, Yuhua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.5
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    • pp.1976-1997
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    • 2016
  • This paper investigates the problem of co-tier interference mitigation for dynamic small- cell networks, in which the load of each small-cell varies with the number of active associated small-cell users (SUs). Due to the fact that most small-cell base stations (SBSs) are deployed in an ad-hoc manner, the problem of reducing co-tier interference caused by dynamic loads in a distributed fashion is quite challenging. First, we propose a new distributed channel allocation method for small-cells with dynamic loads and define a dynamic interference graph. Based on this approach, we formulate the problem as a dynamic interference graph game and prove that the game is a potential game and has at least one pure strategy Nash equilibrium (NE) point. Moreover, we show that the best pure strategy NE point minimizes the expectation of the aggregate dynamic co-tier interference in the small-cell network. A distributed dynamic learning algorithm is then designed to achieve NE of the game, in which each SBS is unaware of the probability distributions of its own and other SBSs' dynamic loads. Simulation results show that the proposed approach can mitigate dynamic co-tier interference effectively and significantly outperform random channel selection.