• The KIPS Transactions:PartA
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• v.16A no.4
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• pp.299-306
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• 2009

Hierarchical Folded HyperStar Network has lower network cost than HCN(n,n) and HFN(n,n) which are hierarchical networks with the same number of nodes. In this paper, we analyze embedding between Hierarchical Folded HyperStar HFH($C_n,C_n$) and Hypercube, HCN(n,n), HFN(n,n). The results of embedding are that HCN(n,n), HFN(n,n) and Hypercube $Q_{2n}$ can be embedded into HFH($C_n,C_n$) with expansion $\frac{C^n}{2^{2n}}$ and dilation 2, 3, and 4, respectively. Also, HFH($C_n,C_n$) can be embedded into HFN(2n,2n) with dilation 1. These results mean so many developed algorithms in Hypercube, HCN(n,n), HFN(n,n) can be used efficiently in HFH($C_n,C_n$).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.240-241
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• 2005

In this paper, Latin Hypercube Sampling based the neural network model for the electrical characteristics of $HfO_2$ thin films grown by metal organic molecular beam epitaxy was investigated. The accumulation capacitance and the hysteresis index are extracted to be the main responses to examine the characteristics of $HfO_2$ thin films. X-ray diffraction was used to analyze the characteristic variation for the different process conditions. The initial weights and biases are selected by Latin Hypercube Sampling method. This modeling methodology can allow us to optimize the process recipes and improve the manufacturability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.701-706
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• 2006

System-level diagnosis plays an important technique for fault detection in multi-processor systems. Efficient diagnosis is very important for real time systems as well as multiprocessor systems. Feng(1) proposed two adaptive diagnosis algorithms HADA and IHADA for hypercube system. The diagnosis cost, measured by diagnosis time and the number of test links, depends on the number and location of the faults. In this paper, we propose an adaptive diagnosis algorithm using the syndrome analysis. This removes unnecessary overhead generated in HADA and IHADA algorithm sand give a better performance compared to Feng's Method.

• Advances in aircraft and spacecraft science
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• v.6 no.6
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• pp.529-550
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• 2019

The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4343-4355
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• 2014

Multicast group communication has many advantages in data centers and thus is widely used by many applications. It can efficiently reduce the network traffic and improve the application throughput. For the multicast application in data centers, an essential problem is how to find a minimal multicast tree, which has been proved to be NP-hard. In this paper, we propose an approximation tree-building method for the minimal multicast problem, named HD（Hamming Distance）-based multicast tree. Consider that many new network structures have been proposed for data centers. We choose three representative ones, including BCube, FBFLY, and HyperX, whose topological structures can be regarded as the generalized hypercube. Given a multicast group in BCube, the HD-based method can jointly schedule the path from each of receiver to the only sender among multiple disjoint paths; hence, it can quickly construct an efficient multicast tree with the low cost. The experimental results demonstrate that our method consumes less time to construct an efficient multicast tree, while considerably reduces the cost of the multicast tree compared to the representative methods. Our approach for BCube can also be adapted to other generalized hypercube network structures for data centers after minimal modifications.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.157-166
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• 2001

A simulation package has been developed as an event-driven system that can handle the hardware configuration of STC104 and algorithm proposed in the sister paper of ‘Study on High Speed Routers(II).’After various STC104 topology of meshes, torus, and hypercubes are constructed using up to 512 switches, the performance of each topology has been analyzed under different message generation rate in terms of throughputs, latency, and packet blocking time. Modified multicast algorithms for STC104 have been proposed for STC104 after U-mesh and U-torus in order to overcome the multicasting difficulty because of the point-to-point communication method found in STC104. The performance of the multicast algorithms have been analyzed over meshes and torus configuration. Throughput gets higher in the order of mesh, torus, and hypercube. Throughput difference among topology were distinctive in the zone of high message generation rate. Latency and blocking time increased in the order of hypercube, torus, and mesh. U-mesh and U-torus of software multicast showed similar throughput, however, U-mesh peformed slightly better result. These algorithms showed eight to ten times better results compared to individual message pass for 90 destination nodes. Multi-link environment also showed better performance than single-link environment because multi-link network used the extra links for communication.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.59-74
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• 2007

Computer simulation models are in general quite complex and time-consuming to run, and therefore, a simpler meta-model is usually constructed for further analysis. In this paper, JANUS, a war-game simulator, is used to describe a certain tank combat situation. Then, second-order response surface and artificial neural network meta-models are developed using the data from eight different experimental designs. Relative performances of the developed meta-models are compared in terms of the mean squared error of prediction. Computational results indicate that, for the given problem, the second-order response surface meta-model generally performs better than the neural network, and the orthogonal array-based Latin hypercube design(LHD) or LHD using maximin distance criterion may be recommended.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.115-124
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• 2014

Hypercube and star graph are widely known as interconnection network. The embedding of an interconnection network is a mapping of a network G into other network H. The possibility of embedding interconnection network G into H with a low cost, has an advantage of efficient algorithms usage in network H, which was developed in network G. In this paper, we provide an embedding algorithm between HCN and HON. HCN(n,n) can be embedded into HON($C_{n+1},C_{n+1}$) with dilation 3 and HON($C_d,C_d$) can be embedded into HCN(2d-1,2d-1) with dilation O(d). Also, star graph can be embedded to half pancake's value of dilation 11, expansion 1, and average dilation 8. Thus, the result means that various algorithms designed for HCN and Star graph can be efficiently executed on HON and half pancake, respectively.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.130-137
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• 2003

This paper presents the problem of partitioning the Single-Stage Shuffle-Exchange Network(SSEN). An algorithm, named SSEN_to_PSEN, is devised to transform an SSEN into a Partitionable Shuffle-Exchange Network (PSEN). The proposed algorithm presents that the SSEN can be partitioned into independent sub-networks without additional links for N $\leq$ 8. Additional links are needed in order to partition an SSEN, but only when N $\geq$ 16. The running time of the algorithm SSEN_to_PSEN is $\theta$(NlogN). By comparing with a hypercube network, the PSEN is less expensive than a hypercube network even when some additional links are added. By partitioning, a large PSEN in a massively parallel machine can compute various problems for multiple users simultaneously, thereby the processing efficiency of the machine is improved.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.1930-1939
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• 1997

In this paper, we analyze the fault diameter and fault tolerance of Gray cube proposed recently in [12]. fault diameter of an interconnection network is one of the important network measures concerning the distance between nodes when some nodes fail. It is showed that fault diameter of n-dimensional Gray cube having $2^n$ nodes is [(n+1)/2]+2, ($n{\ge}3$). It means the increment of the longest distance between nodes under node-failure is only constant factor. Comparing the result with the fault diameter of well-known hypercube, the longest routing distance of a message in a Gray cube under node-failure is about the half of that hypercube.