• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.825-836
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• 2016

In this paper, a speed-up technique for the non-local means (NLM) image denoising method based on local binary descriptor (LBD) is proposed. In the NLM, most of the computation time is spent on searching for non-local similar patches in the search window. The local binary descriptor which represents the structure of patch as binary strings is employed to speed up the search process in the NLM. The descriptor allows for a fast and accurate preselection of non-local similar patches by bitwise operations. Using this approach, a tradeoff between time-saving and noise removal can be obtained. Simulations exhibit that despite being principally constructed for speed, the proposed algorithm outperforms in terms of denoising quality as well. Furthermore, a parallel implementation on GPU brings NLM-LBD to real-time image denoising.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.157-163
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• 2017

The binary and interpolation search algorithms are the most famous among search area algorithms, the former running in $O(log_2n)$ on average, and the latter in $O(log_2log_2n)$ on average and O(n) at worst. Also, the interpolation search use only the probability of key value location without priori information. This paper proposes another search algorithm, which I term a 'hybrid block and interpolation search'. This algorithm employs the block search, a method by which MSB index of a data is determined as a block, and the interpolation search to find the exact location of the key. The proposed algorithm reduces the search range with priori information and search the reduced range with uninformed situation. Experimental results show that the algorithm has a time complexity of $O(log_2log_2n_i)$, $n_i{\simeq}0.1n$ both on average and at worst through utilization of previously acquired information on the block search. The proposed algorithm has proved to be approximately 10 times faster than the interpolation search on average.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.3-4
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• 2006

Fast IP address lookup in routers is essential to achieve packet forwarding in wire-speed. The longest prefix matching for IP address lookup is more complex than exact matching because of its dual dimensions, length and value. By thoroughly studying the current proposals for IP address lookup, we find out that the binary search could be a low-cost solution while providing high performance. Most of the existing binary search algorithms based on trie have simple data structures which can be easily implemented, but they have some problems because of empty internal nodes. The proposed algorithm is based on trie structure, but empty internal nodes are replaced by priority prefixes. The best-matching-prefix search in the proposed algorithm is more efficiently performed since search can be finished earlier when input is matched with a priority prefix. The performance evaluation results show that the constructed priority-trie has very good performance in the lookup speed and the scalability.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.363-371
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• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.8
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• pp.55-62
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• 2004

This paper proposes and analyzes two anti-collision algorithms in Ubiquitous ID system. We mathematically compares the performance of the proposed algorithms with that of binary search algorithm slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center. We also validated analytic results using OPNET simulation. Based on analytic result comparing the proposed Modified bit-by-bit binary tree algorithm with bit-by-bit binary tree algorithm which is the best of existing algorithms, the performance of Modified bit-by-bit binary tree algorithm is about 5% higher when the number of tags is 20, and 100% higher when the number of tags is 200. Furthermore, the performance of proposed Enhanced bit-by-bit binary tree algorithm is about 335％ and 145% higher than Modified bit-by-bit binary tree algorithm for 20 and 200 tags respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1635-1641
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• 2021

Portable systems with built-in active noise control is required low power operation. Excessive anti noise search operation can lead to rapid battery consumption. A method that can adaptively cancel noise according to the operating conditions of the system is required and the methods of reducing power are becoming very important key feature in today's portable systems. In this paper, we propose the method of active noise control(ANC) using binary search algorithm in noisy systems. The implemented architecture detects a frequency component considered as noise from the input signal and by using the binary search algorithm, the system find out an appropriate amplitude value for anti-noise in a much faster time than the general linear search algorithm. Through the experimental results, it was confirmed that the proposed algorithm performs a successful functional operation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.245-257
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• 2012

As one of the most challenging tasks in designing the Internet routers, packet classification is required to achieve the wire-speed processing for every incoming packet. Packet classification algorithm which applies binary search on trie levels to the area-based quad-trie is an efficient algorithm. However, it has a problem of unnecessary access to a hash table, even when there is no node in the corresponding level of the trie. In order to avoid the unnecessary off-chip memory access, we proposed an algorithm using Bloom filters along with the binary search on levels to multiple disjoint tries. For ACL, FW, IPC sets with about 1000, 5000, and 10000 rules, performance evaluation result shows that the search performance is improved by 21 to 33 percent by adding Bloom filters.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.235-242
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• 2012

In RFID System, one of the problem that we must slove is to devise a good anti-collision algorithms to improve the efficiency of tag identification which is usually low because of tag collision. Among of the existing RFID anti-collision algorithm, BS (Binary Search) algorithm, though simple, has a disadvantage that the stage of times used to identify the tags increase exponentially as the number of tags does. In this paper, I propose a new anti-collision algorithm called Multi-collision reflected frame which restricts the number of stages and decided bit. Since the proposal algorithm keep the length size of UID and density of total tag when have 100%. The simulation results showed that the proposed algorithm improves the efficiency by 30~50% compared to the existing algorithm.