• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.195-205
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• 2004

To the unconstrained programme of non-convex function, this article give a modified BFGS algorithm. The idea of the algorithm is to modify the approximate Hessian matrix for obtaining the descent direction and guaranteeing the efficacious of the quasi-Newton iteration pattern. We prove the global convergence properties of the algorithm associating with the general form of line search, and prove the quadratic convergence rate of the algorithm under some conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.756-763
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• 2014

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2470-2476
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• 1997

We propose a new real-time search algorithm and provide experimental evaluation and comparison of the new algorithm with mini-min lookahead algorithm. Many other real-time heuristic-search approached often divide the problem space to several sub-problems. In this paper, the proposed algorithm guarantees not only the sub-problem deadline but also total deadline. Several heuristic real-time search algorithms such as $RTA^{\ast}$, SARTS and DYNORA have been proposed. The performance of such algorithms depend on the quality of their heuristic functions, because such algorithms estimate the search time based on the heuristic function. In real-world problem, however, we often fail to get an effective heuristic function beforehand. Therefore, we propose a new real-time algorithm that determines the sub-problem deadline based on the status of search space during sub-problem search process. That uses the cut-off method that is a dynamic stopping-criterion-strategy to search the sub-problem.

• Journal of Families and Better Life
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• v.7 no.1
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• pp.15-25
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• 1989

The purpose of this study is to examine the factors affecting the consumer's search for information and the relationship between the amount of search and the final price paid. The model indicates the demand for search is affected by the market price of each durable good purchased, the tim available for search, family income, direct cost of search, the initial stock of information, effectiveness of search, and shopping attitudes. The final price savings are a function of search, price of dispersion in the market, the initial stock of information, and effectiveness of search. Data from the Pane Study on Consumer Decisions and Asset Management were used for the empirical testing of the theoretical model. The amount of information search as dependent variable is represented by two different measures, the level of discussion with others and the number of stores visited. The amount of discussion with others depends mainly on the respondent's shopping attitude. The higher the wife's desire to search, the higher the degree of husband's comparison shopping, the less the husband's perception of price-quality relationship, the higher the level of discussions with others. The number of stores visited depends on the average market price of product purchased and the level of family income. The higher the average market price and he higher the level of family income, the greater the number of stores visited. The final savings depend upon the level of information search. The greater the number of store visited, but the less the purchase is discussed with stores, the higher the final savings are.

• Journal of Information Science Theory and Practice
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• v.3 no.4
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• pp.19-34
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• 2015

Evaluation of retrieval systems is mostly limited to laboratory settings and rarely considers changes of performance over time. This article presents an evaluation of retrieval systems for internal Web site search systems between the years 2006 and 2011. A holistic evaluation methodology for real Web sites was developed which includes tests for functionality, search quality, and user interaction. Among other sites, one set of 20 Web site search systems was evaluated three times in different years and no substantial improvement could be shown. It is surprising that the communication between site and user still leads to very poor results in many cases. Overall, the quality of these search systems could be improved, and several areas for improvement are apparent from our evaluation. For a comparison, Google’s site search function was also tested with the same tasks.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.71-82
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• 2012

Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.101-104
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• 2002

This paper propose that is algorithm of power dissipation reduction in the high level synthesis design for DSP(Digital Signal Processor), as the portable terminal system recently demand high power dissipation. This paper obtain effect of power dissipation reduction and switching activity that increase correlation of operands as input data of function unit. The algorithm search loop or repeatedly data to the input operands of function unit. That can be reduce the power dissipation using the new low power high level synthesis algorithm. In this Paper, scheduling operation search same nodes from input DFG(Data Flow Graph) with correlation coefficient of first input node and among nodes. Function units consist a multiplier, an adder and a register. The power estimation method is added switching activity for each bits of nodes. The power estimation have good efficient using proposed algorithm. This paper result obtain more Power reduction of fifty percents after using a new low power algorithm in a function unit as multiplier.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.13-16
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• 2004

This paper deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection award, if detected, which represents the detection priority of target and is non-increasing with time. The objective is to establish the optimal search plan which allocates the search resource effort over the search areas in each time interval in order to maximize the total detection award. In the analysis, the given problem is decomposed into intervalwise individual search problems each being treated as a single stationary target problem for each time interval. An associated iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.405-415
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• 2020

With the increase in smartphone user, mobile forensics has become an essential element in modern digital forensic investigation. Mobile messenger data is very important data in mobile forensics because it can acquire information such as user's life pattern and mental state. In order to analyze messenger data, a decryption technique of an encrypted messenger data is required. Since most messengers provide a message deleting function, a technique for recovering deleted messages is required. WeChat Messenger, a messenger used by about 1 billion people around the world, uses IMEI (International Mobile Equipment Identity) information to encrypt data and provides message deletion function. In this paper, we propose a data decryption method in the absence of IMEI information and propose a method for recovering deleted messages using FTS (Full Text Search) database created for full-text search function of SQLite database.