• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.5
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• pp.11-17
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• 1998

In this paper, the synthesis procedufe of impedance matching network is presented for broad-band microwave amplifier design, whereby amplifier operating in the octave bandwidth is designed and fabricated in detail. The transfer function of the matching netowrks is synthesized by chebyshev approximation and element values for the networks of specified topology are calculatd for various MILs and ripples. After the transistor is modeled by negative-image device model, the synthesis procedure for matching networks is applied to broad-band amplifier design which has electrical performance of about 12dB gain in 4 to 8GHz range. Experimental results obtained from the fabricated amplifier are shown to approach the electrical performance designed in the given frequency range. Construction of the impedance matching networks by transfer function synthesis is very useful method for the design of broad-band microwave amplifiers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.5-25
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• 2009

In recent years the popularity of multi-hop wireless networks has been growing. Its flexible topology and abundant routing path enables many types of applications. However, the lack of a centralized controller often makes it difficult to design a reliable service in multi-hop wireless networks. While packet routing has been the center of attention for decades, recent research focuses on data discovery such as file sharing in multi-hop wireless networks. Although there are many peer-to-peer lookup (P2P-lookup) schemes for wired networks, they have inherent limitations for multi-hop wireless networks. First, a wired P2P-lookup builds a search structure on the overlay network and disregards the underlying topology. Second, the performance guarantee often relies on specific topology models such as random graphs, which do not apply to multi-hop wireless networks. Past studies on wireless P2P-lookup either combined existing solutions with known routing algorithms or proposed tree-based routing, which is prone to traffic congestion. In this paper, we present two wireless P2P-lookup schemes that strictly build a topology-dependent structure. We first propose the Ring Interval Graph Search (RIGS) that constructs a DHT only through direct connections between the nodes. We then propose the ValleyWalk, a loosely-structured scheme that requires simple local hints for query routing. Packet-level simulations showed that RIGS can find the target with near-shortest search length and ValleyWalk can find the target with near-shortest search length when there is at least 5% object replication. We also provide an analytic bound on the search length of ValleyWalk.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.11
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• pp.830-835
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• 2006

Because of its exponential growth of data and voice transmissions through wireless communications, efficient resource management became more important factor when we design wireless networks. One of those limited resources in the wireless communications is frequency bandwidth. As a solution of increasing reusability of resources, the efficient frequency assignment problems on wireless networks have been widely studied. One suitable approach to solve these frequency assignment problems is transforming the problem into traditional graph coloring problems in graph theory. However, most of frequency assignments on arbitrary network topology are NP-Complete problems. In this paper, we consider the Chromatic Bandwidth Problem on the cellular topology wireless networks. It is known that the lower bound of the necessary number of frequencies for this problem is $O(k^2)$. We prove that the lower bound of the necessary number of frequencies for the Chromatic Bandwidth Problem is $O(k^3)$ which is tighter lower bound than the previous known result.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1230-1237
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• 2009

In this paper, we develop a design methodology of Granular-based Radial Basis Function Neural Networks(GRBFNN) by context-based clustering. In contrast with the plethora of existing approaches, here we promote a development strategy in which a topology of the network is predominantly based upon a collection of information granules formed on a basis of available experimental data. The output space is granulated making use of the K-Means clustering while the input space is clustered with the aid of a so-called context-based fuzzy clustering. The number of information granules produced for each context is adjusted so that we satisfy a certain reconstructability criterion that helps us minimize an error between the original data and the ones resulting from their reconstruction involving prototypes of the clusters and the corresponding membership values. In contrast to "standard" Radial Basis Function neural networks, the output neuron of the network exhibits a certain functional nature as its connections are realized as local linear whose location is determined by the values of the context and the prototypes in the input space. The other parameters of these local functions are subject to further parametric optimization. Numeric examples involve some low dimensional synthetic data and selected data coming from the Machine Learning repository.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.56-63
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• 2000

In this paper, we design new high performance ATM switch architectures based on a Generalized Shuffle network(GSN). The GSN is a distributed network topology with the number of nodes in O(N). To improve the throughput of the switch, a layering strategy called Weaved GSN(WGSN). WGSN has an additional connection links between switching elements which locate in the same position of adjacent GSNs. The analysis and simulation are performed under uniform and full load conditions, and the results show that the proposed switch has better throughput and cell loss performance when compared with other banyan-based switch architectures known so far.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8B
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• pp.812-821
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• 2009

This paper proposes a novel dynamically reconfigurable switch for various multimedia applications in hybrid NoC systems. Current NoC systems, which adopt hybrid NoC structure with fixed switch and job distribution algorithms, require designers to precisely predict the property of applications to be processed. This paper proposes a reconfigurable switch which minimizes buffer overflow in various multimedia applications running on an NoC system. To verify the performance of the proposed system, we performed experiments on various multimedia applications running on embedded systems, such as MPEG4 and MP3 decoder, GPS positioning system, and OFDM demodulator. Experimental results show that buffer overflow has been decreased by 41.8% and 29.0%, respectively, when compared with NoC systems having sub-clusters with mesh or star topology. Power usage has been increased by 2.3% compared with hybrid NoC systems using fixed switches, and chip area has been increased from -0.6% to 5.7% depending on sub-cluster topology.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.255-260
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• 2008

In the recently years, there has been a big interest in ad hoc wireless network as they have tremendous military and commercial potential. An Ad hoc wireless network is composed of mobile computing devices that use having no fixed infrastructure of a multi-hop wireless network formed. So, the fact that limited resource could support the network of robust, simple framework and energy conserving etc. In this paper, we propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. And the ontology clustering adopts a tree structure to enhance resilient against mobility and routing complexity. This proposed multicast routing protocol utilizes node locality to be improve the flexible connectivity and stable mobility on local discovery routing and flooding discovery routing. Also attempts to improve route recovery efficiency and reduce data transmissions of context-awareness. We also provide simulation results to validate the model complexity. We have developed that proposed an algorithm have design multi-hierarchy layered networks to simulate a desired system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.201-208
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• 2010

Mobile Ad Hoc Network(MANET) has highly dynamic topology, hence presents a great challenge on the network performance evaluation and network protocol design. We proposed total path break up time, $\sum_{i}T_i$, as a metric to measure the performance of the total system as well as an individual connection. In this paper, we evaluate and analyze the performance of three mobility models(Random Waypoint, Manhattan, Blocked Manhattan) by applying the total path break up metric, investigate why network parameters such as packet delivery ratio, end-to-end delay, etc. vary by mobility models. We also present analysis result how much AODV Buffer improve packet delivery ratio and increase the end-to-end delay in spite of the path break up.