• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.7-22
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• 2015

This paper describes a Web search optimization study that investigates both static and dynamic tuning methods for optimizing system performance. We extended the conventional fusion approach by introducing the "dynamic tuning" process with which to optimize the fusion formula that combines the contributions of diverse sources of evidence on the Web. By engaging in iterative dynamic tuning process, where we successively fine-tuned the fusion parameters based on the cognitive analysis of immediate system feedback, we were able to significantly increase the retrieval performance. Our results show that exploiting the richness of Web search environment by combining multiple sources of evidence is an effective strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4658-4679
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• 2017

Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.229-236
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• 2018

Purpose: Makgeolli is a traditional alcoholic beverage made from rice with a fermentation starter called "nuruk." The concentration of alcohol in makgeolli depends on the temperature of the fermentation tank. It is important to monitor the alcohol concentration to manage the makgeolli production process. Methods: Data were collected from 84 makgeolli fermentation tanks over a year period. Independent variables included the temperatures of the tanks and the room where the tanks were located, as well as the quantity, acidity, and water concentration of the source. Software for the multilayer perceptron model (MLP) was written in Python using the Scikit-learn library. Results: Many models were created for which the optimization converged within 100 iterations, and their coefficients of determination $R^2$ were considerably high. The coefficient of determination $R^2$ of the best model with the training set and the test set were 0.94 and 0.93, respectively. The fact that the difference between them was very small indicated that the model was not overfitted. The maximum and minimum error was approximately 2% and the total MSE was 0.078%. Conclusions: The MLP model could help predict the alcohol concentration and to control the production process of makgeolli. In future research, the optimization of the production process will be studied based on the model.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.197-205
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• 2013

In this study, we developed a program of optimizing stand-level carbon stock using a stand-level yield model and the Simulated Annealing (SA) heuristic method to derive a optimized forest treatment solution. The SA is one of the heuristic algorithms that can provide a desirable management solution when dealing with various management purposes. The SA heuristic algorithm applied 'thermal equilibrium test', a thresholds approach to solve the phenomenon that does not find an optimum solution and stays at a local optimum value during the process. We conducted a sensitivity test for the temperature reduction rate, the major parameter of the thermal equilibrium test, to analyze its influence on the objective function value and the total iteration of the optimization process. Using the developed program, three scenarios were compared: a common treatment in forestry (baseline), the optimized solution of maximizing the amount of harvest(alternative 1), and the optimized solution of maximizing the amount of carbon stocks(alternative 2). As the results, we found that the alternative 1 showed provide acceptable solutions for the objectives. From the sensitivity test, we found that the objective function value and the total iteration of the process can be significantly influenced by the temperature reduction rate. The developed program will be practically used for optimizing stand-level carbon stock and developing optimized treatment solutions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.119-124
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• 2009

In this paper, AMR-WB+ audio coder is implemented, in real-time, using Intel 400MHz Xscale PXA250 with 32bit RISC processor ARM9E-J(R)core. The assembly code for ARM9E-J(R)core is developed through the serial process of C code optimization, cross compile, assembly code manual optimization and adjusting the optimized code to Embedded Visual C++ platform. C code is trimmed on Visual C++ platform. Cross compile and assembly code manual optimization are performed on CodeWarrior with ARM compiler. Through these stages the code for both ARM EVM board and PDA is implemented. The average complexities of the code are 160.75MHz on encoder and 33.05MHz on decoder. In case of static link library(SLL), the required memories are 65.21Kbyte, 32.01Kbyte and 279.81Kbyte on encoder, decoder and common sources, respectively. The implemented coder is evaluated using 16 test vectors given by 3GPP to verify the bit-exactness of the coder.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.5
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• pp.94-99
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• 2010

This paper presents a design procedure of digitally controlled oscillator(DCO) for power optimization. By controlling coarse tuning bits and fine tuning bits of DCO, the proposed design procedure can optimize the power dissipation and does not affect the LSB resolution, frequency range, linearity, portability. For optimization, the relationship between control bits and power dissipation of the DCO was analyzed. The DCO circuits using and unusing proposed design technique have been designed, simulated and proved using 0.13um, 1.2V CMOS library. The DCO circuit with proposed design technique has operation range between 283MHz and 1.1GHz and has 1.7ps LSB resolution and consumes 2.789mW at frequency of 1GHz.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.420-427
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• 2004

This paper presents real time implementation of 4kbps EHSX (Enhanced Harmonic Stochastic Excitation) speech coder that combines the harmonic vector excitation coding with time-separated transition coding. The harmonic vector excitation coding uses the harmonic excitation coding for voiced frames and used the vector excitation coding with the structure of analysis-by-synthesis for unvoiced frames, respectively. For transition frames mixed with voiced and unvoiced signal, we use the time-separated transition coding. In this paper. we present the optimization methods of implementation speech coder on the EMS320C6701/sup (R)/ DSP. To reduce the complex for real-time implementation. we perform the optimization method in algorithm by replacing the complex sinusoidal synthesis method with IFFT. and we apply fully pipelines hand assembly coding after converting it from floating source to fixed source. To generate a more efficient code. we also make use or the available EMS320C6701/sup (R)/ resources such as Fastest67x library and memory organization.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.1
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• pp.1-7
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• 2003

The aerodynamic optimization method for airfoil design was described in this paper. The Navier-Stokes equations were solved to consider the viscous flow information around an airfoil. The Modified Method of Feasible Direction(MMFD) was used for sensitivity analysis and the polynomial interpolation was used for distance calculation of the minimization. The Message Passing Interface(MPI) library of parallel computation was adopted to reduce the computation time of flow solver by decomposing the entire computational domain into 8 sub-domains and one-to-one allocating 8 processors to 8 sub-domains. The parallel computation was also used to compute the sensitivity analysis by allocating each search direction to each processor. The present optimization reduced the drag of airfoil while the lift is maintained at the tolerable design value.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• Biotechnology and Bioprocess Engineering:BBE
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• v.7 no.3
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• pp.121-129
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• 2002

Existing methods for optimization of sequences by random mutagenesis generate libraries with a small number of mostly deleterious mutations, resulting in libraries containing a large fraction of non-functional clones that explore only a small part of sequence space. Large numbers of clones need to be screened to find the rare mutants with improvements. Library display formats are useful to screen very large libraries but impose screening limitations that limit the value of this approach for most commercial applications. By contrast, in both classical breeding and in DNA shuffling, natural diversity is permutated by homologous recombination, generating libraries of very high quality, from which improved clones can be identified with a small number of complex screens. Given that this small number of screens can be performed under the conditions of actual use of the product, commercially relevant improvements can be reliably obtained.