• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.217-222
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• 2014

In this paper, I propose an efficient data search system using data partitioning algorithm in Microsoft Excel. I propose searching algorithm to retrieve data quickly using VBA functioning in the Excel. This algorithm is to specify the sheet you are looking for. Once the sheet is specified, the algorithm searches the beginning and the end of the data in the sheet. The algorithm compares intermediate values and key words, from the starting position of the cell. In this way, it will search data to the end. This proposed algorithm was implemented and tested in the Excel system using VBA program. The experimental results showed that the performance was better than that of the conventional sequential search method.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1011-1014
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• 1999

In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.671-674
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• 2013

In this paper, we propose an efficient data search system using data partitioning algorithm in Microsoft Excel. We propose to retrieve the data quickly using VBA functioning Excel. This algorithm is to specify the sheet you are looking for. Once the sheet is specified, it searches the beginning and the end of the data in the sheet. It compares desired key words and intermediate values, starting from the position of the cell. In this way, it will search data to the end. This proposed algorithm was implemented and tested using actual VBA program. The experimental results showed that the performance was more excellent than that of the conventional search method.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.891-897
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• 2021

In this paper, we propose a destination optimal route algorithm for providing route finding service for the transportation handicapped by using the multi-criteria decision-making technique and the modified A-STAR optimal route search algorithm. This is a method to set the route to the destination centering on safety by replacing the distance cost of the existing A-STAR optimal route search algorithm with the safety cost calculated through AHP/TOPSIS analysis. To this end, 10 factors such as road damage, curb, and road hole were first classified as poor road factors that hinder road driving, and then pairwise comparison of AHP was analyzed and then defined as the weight of TOPSIS. Afterwards, the degree of driving safety was quantified for a certain road section in Busan through TOPSIS analysis, and the development of an optimal route search algorithm for the transportation handicapped that replaces the distance cost with safety in the finally modified A-STAR optimal route algorithm was completed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.747-752
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• 2004

Researches about scheduling of the distributed real-time systems have been proposed. However, they have some weak points, not scheduling both sporadic and periodic tasks and messages or being unable to guaranteeing the end-to-end constraints due to omitting precedence relations between sporadic tasks. So this paper proposes a new scheduling method for distributed real-time systems consisting of sporadic and periodic tasks with precedence relations and sporadic and periodic messages, guaranteeing end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic (RM) scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.175-185
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• 2005

The scheduling methods of the distributed real-time systems have been proposed. However, they have some weak points. They did not schedule both sporadic and periodic tasks and messages at the same time or did not consider the end-to-end constraints such as precedence relations between sporadic tasks. This means that system scheduling must guarantee the constraints of practical systems and be applicable to them. This paper proposes a new scheduling method that can be applied to more practical model of distributed real-time systems. System model consists of sporadic and periodic tasks with precedence relations and sporadic and periodic messages and has end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1609-1615
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• 2006

Overlay multicast technique is an effective way as an alternative to IP multicast. Traditional IP multicast is not widely deployed because of the complexity of IP multicast technology and lack of application. But overlay multicast can be easily deployed by effectively reducing complexity of network routers. Because overlay multicast resides on top of densely connected IP network, In case of multimedia streaming service over overlay multicast tree, real-time data is sensitive to end-to-end delay. Therefore, moderate algorithm's development to this network environment is very important. In this paper, we are interested in minimizing maximum end-to-end delay in overlay multicast tree. The problem is formulated as a degree-bounded minimum delay spanning tree, which is a problem well-known as NP-hard. We develop tabu search heuristic with intensification and diversification strategies. Robust experimental results show that is comparable to the optimal solution and applicable in real time

• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• Journal of KIISE
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• v.42 no.8
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• pp.961-971
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• 2015

As a representative area-decomposed algorithm, an area-based quad-trie (AQT) has an issue of search performance. The search procedure must continue to follow the path to its end, due to the possibility of the higher priority-matching rule, even though a matching rule is encountered in a node. A leaf-pushing AQT improves the search performance of the AQT by making a single rule node exist in each search path. This paper proposes a new algorithm to further improve the search performance of the leaf-pushing AQT. The proposed algorithm implements a leaf-pushing AQT using a hash table and an on-chip Bloom filter. In the proposed algorithm, by sequentially querying the Bloom filter, the level of the rule node in the leaf-pushing AQT is identified first. After this procedure, the rule database, which is usually stored in an off-chip memory, is accessed. Simulation results show that packet classification can be performed through a single hash table access using a reasonable sized Bloom filter. The proposed algorithm is compared with existing algorithms in terms of the memory requirement and the search performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.209-219
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• 2004

In order to implement a real time hardware for keyword spotting, we propose a Single-End-Point DTW(SEP-DTW) algorithm which is simple and less complex for computation. The SEP-DTW algorithm only needs a single end point which enables efficient applications, and it has a small wont of computations because the global search area is divided into successive local search areas. Also, we adopt new local constraints and a new distance measure for a better performance of the SEP-DTW algorithm. Besides, we make a normalization of feature same vectors so that they have the same variance in each frequency bin, and each frame has the same energy levels. To construct several reference patterns for each keyword, we use a clustering algorithm for all training patterns, and mean vectors in every cluster are taken as reference patterns. In order to detect a key word for input streams of speech, we measure the distances between reference patterns and input pattern, and we make a decision whether the distances are smaller than a pre-defined threshold value. With isolated speech recognition and keyword spotting experiments, we verify that the proposed algorithm has a better performance than other methods.