• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.101-117
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• 2007

In this paper, we propose a customized genetic algorithm (GA) to find the minimum-cost guideway network (GN) of personal rapid transit (PRT) subject to connectivity, reliability, and traffic capacity constraints. PRT is a novel transportation concept, where a number of automated taxi-sized vehicles run on an elevated GN. One of the most important problems regarding PRT is how to design its GN topology for given station locations and the associated inter-station traffic demands. We model the GN as a directed graph, where its cost, connectivity, reliability, and node traffics are formulated. Based on this formulation, we develop the GA with special genetic operators well suited for the GN design problem. Such operators include steady state selection, repair algorithm, and directed mutation. We perform numerical experiments to determine the adequate GA parameters and compare its performance to other optimization algorithms previously reported. The experimental results verify the effectiveness and efficiency of the proposed approach for the GN design problem having up to 210 links.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2196-2203
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• 1999

This paper describes the bus scheduling problem and register optimization method in datapath synthesis. Scheduling is process of operation allocation to control steps in order to minimize the cost function under the given circumstances. For that purpose, we propose some formulations to minimize the cost function for bus assignment to get an optimal and minimal cost function in hardware allocations. Especially, bus and register minimization technique are fully considered which are the essential topics in hardware allocation. Register scheduling is done after the operation and bus scheduling. Experiments are done with the DFG model of fifth-order digital ware filter to show its effectiveness. Structural integer programming formulations are used to solve the scheduling problems in order to get the optimal scheduling results in the integer linear programming environment.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.141-152
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• 2007

Selectivity estimation has been a crucial component in query optimization in relational databases. While extensive researches have been done on this topic for the predicates of numerical data, only little work has been done for substring predicates. We propose novel suffix tree transform algorithms for this problem. Unlike previous approaches where a full suffix tree is pruned and then an estimation algorithm is employed, we transform a suffix tree into a suffix graph systematically. In our approach, nodes with similar counts are merged while structural information in the original suffix tree is preserved in a controlled manner. We present both an error-bound algorithm and a space-bound algorithm. Experimental results with real life data sets show that our algorithms have lower average relative error than that of the previous works as well as good error distribution characteristics.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1345-1356
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• 1998

Prolog tailoring technique, an optimization method to improve the execution speed of a procedure, is proposed in this paper. When a procedure is frequently and repeatedly called and the machine has a lot of callee-saved registers, optimizing prolog and epilog can become an important step of optimization. Epilg tailoring supported by IBM XL C Compiler has been known to improve procedure's execution speed by reducing register restore instructions on execution paths, but no algorithms for prolog tailoring has been proposed yet. The prolog generated by the prolog tailoring algorithm proposed in this paper executes considerably smaller number of register save instructions at run-time. This means the total number of instructions to be executed is decreased resulting in an improvement on the procedure's execution speed. To maintain the correctness of code, prolog code should not be inserted inside diamond structures of loop structures. This paper proposes a prolog tailoring technique which generates register save instructions at the best position in a control flow graph while not allowing the insertion of any prolog code inside diamond structures of loop structures.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1483-1492
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• 1996

In this paper, related on the postal business with the GIS(Geographics Information System), it discusses design and implementation of the PROS(Postal Route Optimization System) model and its main module, the shortest path generation algorithm, for supporting to postal route managements. It explains examples requirements of postal route system, and suggests the efficient PROS model using our developed shortest path generation algorithm. Because the shortest path algorithm adopts not only consider the Dijkstra algorithm of graph theory, but also the method with the direction property, PROS can be implemented with fast and efficient route search. PROS is mainly constituted of the Shortest Generator, the Isochronal Area Generator, and the Path Rearrangement Generator. It also exploits the GIS engine and the spatial DBMS (Data Base Management System) for processing coordinates in the map and geographical features. PROS can be used in the management of postal delivery business and delivery area and route, and in the rearrangement of route. In the near future, it can be also applied to commercial delivery businesses, guides of routs and traffic informations, and auto navigation system with GPS(Global Positioning System).

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.31-38
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• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.

• Journal of the Korean Chemical Society
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• v.58 no.2
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• pp.198-204
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• 2014

In this present study, bagasse based pulp and paper industry wastewater was treated under different operating conditions such as initial pH (6-8), temperature ($25-35^{\circ}C$) and contact time (3-7 days) by using Bacillus subtilis. Response surface methodology (RSM) coupled with Box-Behnken response surface design (BBD) was employed to investigate the effect of process variables on the responses such as turbidity, biological oxygen demand (BOD) and chemical oxygen demand (COD) removal. The experimental data were analyzed by Pareto analysis of variance (ANOVA) and the second order polynomial models were developed. Interactive effects of the process variables on the responses were studied using plotting 3D response surface contour graph and the optimum process conditions were found to be: initial pH of 7, temperature of $30^{\circ}C$ and contact time of 5 days. Under these conditions, removal efficiencies of turbidity, BOD and COD were found to be 85%, 93% and 80% respectively which are close agreement with real experiments. These results indicate that the treatment of bagasse based pulp and paper industry wastewater using Bacillus subtilis is an effective and novel technique.

• Korean Journal of Medicinal Crop Science
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• v.24 no.4
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• pp.263-270
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• 2016

Background: In this study, microwave extraction was used, which is an effective method to extract useful bioactive substances as it requires low quantities of solvent and short time periods. The aim of this study was to determine the optimal extraction conditions for Agrimonia pilosa Ledeb. Methods and Results: The independent variables were ethanol concentration, microwave power, and extraction time, each of which had five levels. The dependent variables were total polyphenol and total flavonoid content, and DPPH radical scavenging activity. To determine the optimal extraction conditions for bioactive compounds, a response surface methodology was employed. Contour maps were generated from polynomial equations. The optimal conditions were then assumed by superimposing these contour maps. Based on the resulting graph, the optimal microwave extraction conditions for Agrimonia pilosa Ledeb were determined as 42 - 48% ethanol concentration, 240 - 280W microwave power, and 13 - 20 min of extraction time. Conclusions: Ethanol concentration had a significant effect on microwave extraction, in terms of total polyphenol and total flavonoid content, as well as DPPH radical scavenging activity. Microwave power and extraction time influenced the total polyphenol content, but not the total flavonoid content or the DPPH radical scavenging activity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1837-1860
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• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.928-935
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• 2009

Ontology schema reasoning is used to maintain consistency of concepts and build concept hierarchy automatically. For the purpose, the search of concepts must be inevitably performed. Ontology schema reasoning performs the test of subsumption relationships of all the concepts delivered in the test set. The result of subsumption tests is determined based on the creation of complete graphs, which seriously weighs with the performance of reasoning. In general, the process of creating complete graph has been known as expressive procedure. This process is essential in improving the leading performance. In this paper, we propose a method enhancing the classification performance by identifying unnecessary subsumption test supported by optimized searching method on subsumption relationship test among concepts. It is achieved by propagating subsumption tests results into other concept.