• ETRI Journal
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• v.43 no.1
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• pp.64-73
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• 2021

Two-dimensional torus network nodes are typically interconnected using XY routing algorithm for transmitting a packet from a source node to a destination node. In XY routing, if all the paths are used efficiently, the throughput and latency can be improved. In this paper, to utilize all the paths efficiently, we propose a novel binary optical routing algorithm (BORA) to improve the throughput and latency. The throughput is calculated according to the injection rate and number of packets received at the destination. The XY routing algorithm and proposed BORA are implemented using objective modular network testbed in C++ simulation software and the results are analyzed and compared. In this paper, the simulation results show that the network latency reduces to 50% while using the proposed algorithm; moreover, the throughput is also improved.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.91-97
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• 1996

This paper proves by straightforward computation an interesting property of a recursive indexing: it preserves the entropy of a geometrically-distributes stationary memoryless source. This result is a pleasant surprise because the recursive indexing though one-to-one, is a symbol-to-string mapping and the entropy is measured in terms of the source symbols. This preservation of the entropy implies that the minimum average number of bits needed to represent a geometric memoryless source by the recursive indexing followed by a good binary encoder of a finite imput alphabet remains the same as that by a good encoder of an infinite input alphabet. Therefore, the recursive indexing theoretically keeps coding optimality intact. For this reason recursive indexing can provide an interface for a binary code with a finite code book that performs reasonably well for a source with an infinite alphabet.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.247-256
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• 2001

Digital watermarking is a copyright protection technique for digital images which embed a code into the digital data so the data is marked. Watermarking techniques previously deal with on-line digital data and have been developed to withstand digital attacks such image processing, compression and geometric transformation. In this paper we propose a novel method of embedding watermarks in printed images. In the proposed algorithm, watermark is embedded in a dithered binary image by comparing the $2\times{2}$ blocks of the counting array is the number of 1 (WHITE) in the $16\times{16}$ blocks of the dithered binary image with predefined reference block pattern, which is generated by watermark values. The proposed algorithm is able to provide more information at a watermark because the proposed algorithm use both '1'and '0' as watermark values. The watermark information is detected by comparing the watermark which is reconstructed from the image which is embedded watermark with the original watermark which is embedded in a binary image. The performance of the proposed algorithm is compared with that of the conventional watermark embedding algorithm for printed images by detecting watermark for scan images.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.361-371
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• 2008

In this paper, the hypercube, hyperpetersen networks, whose degree is increasing in accordance with expansion of number of node and complete binary tree are one-to-one embedded into peterson-torus(PT) network which has fixed degree. The one-to-one embedding has less risk of overload or idle for the processor comparative to one-to-many and many-to-one embedding. For the algorithms which were developed on hypercube or hyperpetersen are used for PT network, it is one-to one embedded at expansion ${\doteqdot}1$, dilation 1.5n+2 and link congestion O(n) not to generate large numbers of idle processor. The complete binary tree is embedded into PT network with link congestion =1, expansion ${\doteqdot}5$ and dilation O(n) to avoid the bottleneck at the wormhole routing system which is not affected by the path length.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.1-12
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• 1999

A new algorithm of constructing binary decision diagram(BDD) for design verification of switch-level circuits is proposed in this paper. In the switch-level circuit, functions are characterized by serial and parallel connections of switches and the final logic values may have high-impedance and unstable states in addition to the logic values of 0 and 1. We extend the BDD to represent functions of switch-level circuits as acyclic graphs so called switch-level binary decision diagram (SLBDD). The function representation of the graph is in the worst case, exponential to the number of inputs. Thus, the ordering of decision variables plays a major role in graph sizes. Under the existence of pass-transistors and domino-logic of precharging circuitry, we also propose an input ordering algorithm for the efficiency in graph sizes. We conducted several experiments on various benchmark circuits and the results show that our algorithm is efficient enough to apply to functional simulation, power estimation, and fault-simulation of switch-level design.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.527-533
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• 2013

BCI (Brain-Computer Interface) is a system that transforms a subject's brain signal related to their intention into a control signal by classifying EEG (electroencephalograph) signals obtained during the imagination of movement of a subject's limbs. The BCI system allows us to control machines such as robot arms or wheelchairs only by imaging limbs. With the exact same experiment environment, activated brain regions of each subjects are totally different. In that case, a simple approach is to use as many channels as possible when measuring brain signals. However the problem is that using many channels also causes other problems. When applying a CSP (Common Spatial Pattern), which is an EEG extraction method, many channels cause an overfitting problem, and in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest an optimal channel selection method using a BPSO (Binary Particle Swarm Optimization), BPSO with channel impact factor, and GA. This paper examined optimal selected channels among all channels using three optimization methods and compared the classification accuracy and the number of selected channels between BPSO, BPSO with channel impact factor, and GA by SVM (Support Vector Machine). The result showed that BPSO with channel impact factor selected 2 fewer channels and even improved accuracy by 10.17~11.34% compared with BPSO and GA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.321-324
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• 2007

In this paper, the performance improvement of ultra-wideband (UWB) communications system to achieve high-data-rate using spatial diversity provided by multiple receive antennas is investigated. We derive the expression for the received SINR after spatially combining through multiple receive antennas and evaluate the bit error rate (BER) performance by numerical simulation. We also compare the performance results in the case of 2PPM systems with the theoretical performance results in the case of 2PAM THMA UWB systems. The impacts of spatial diversity on the performance of 2PPM and 2PAM THMA UWB systems are analyzed. It is shown that the BER performance is improved as the number of receive antennas increases. Also, it is observed that in the presence of multiple user interference signals, the performance of 2PAM THMA UWB systems is considerably superior to that of 2PPM THMA UWB systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5522-5536
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• 2017

In this paper, a video based smoke detection method using dynamic texture feature extraction with volume local binary patterns is studied. Block based method was used to distinguish smoke frames in high definition videos obtained by experiments firstly. Then we propose a method that directly extracts dynamic texture features based on irregular motion regions to reduce adverse impacts of block size and motion area ratio threshold. Several general volume local binary patterns were used to extract dynamic texture, including LBPTOP, VLBP, CLBPTOP and CVLBP, to study the effect of the number of sample points, frame interval and modes of the operator on smoke detection. Support vector machine was used as the classifier for dynamic texture features. The results show that dynamic texture is a reliable clue for video based smoke detection. It is generally conducive to reducing the false alarm rate by increasing the dimension of the feature vector. However, it does not always contribute to the improvement of the detection rate. Additionally, it is found that the feature computing time is not directly related to the vector dimension in our experiments, which is important for the realization of real-time detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.382-390
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• 2005

Huffman codes are widely used for image and video data transmission. As the increase of real-time data, a lot of studies on effective decoding algorithms and architectures have been done. In this paper, we proposed a balanced binary search tree for Huffman decoding and compared the performance of the proposed architecture with that of previous works. Based on definitions of the comparison of codewords with different lengths, the proposed architecture constructs a balanced binary tree which does not include empty internal nodes, and hence it is very efficient in the memory requirement. Performance evaluation results using actual image data show that the proposed architecture requires small number of table entries, and the decoding time is 1, 5, and 2.41 memory accesses in minimum, maximum, and average, respectively.