• Annual Conference of KIPS
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• 2006.05a
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• pp.1117-1120
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• 2006

Wide applications because of their flexibilities and conveniences of Wireless Mobile Ad-hoc Networks (MANETs) also make them more interesting to adversaries. Currently, there is no applied architecture efficient enough to protect them against many types of attacks. Some preventive mechanisms are deployed to protect MANETs but they are not enough. Thus, MANETs need an Intrusion Detection System (IDS) as the second layer to detect intrusion of adversaries to response and diminish the damage. In this paper, we propose an algorithm for detecting bogus nodes when they attempt to intrude into network by attack routing protocol. In addition, we propose a procedure to find the most optimize path between two nodes when they want to communicate with each other. We also show that our algorithm is very easy to implement in current proposed architectures.

• ETRI Journal
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• v.31 no.6
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• pp.806-808
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• 2009

A new computationally efficient algorithm-based propagator method for two-dimensional (2-D) direction-of-arrival (DOA) estimation is proposed, which uses two parallel uniform linear arrays. The algorithm takes advantage of the special structure of the array which enables 2-D DOA estimation without pair matching. Simulation results show that the proposed algorithm achieves very accurate estimation at a computational cost 4 dB lower than that of standard methods.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.37-39
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• 2007

This paper compared with field weakening operation methods for the spindle motor of machine tool in which high speed drive is required. The maximum torque field weakening algorithm ensures the full utilization of the output torque capability of the machine over 1/Wr method. From simulation, the validity of the Max_Te method is confirmed. It is verified that the Max-Te algorithm provided the improved torque capability over 1/Wr method. So, It is applicable to provide high performance control involving fast acceleration and precise speed control for the adjustable speed drive system of spindle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1128-1145
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• 2022

Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.

• International Journal of Contents
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• v.8 no.2
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• pp.19-22
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• 2012

New and handoff calls control mechanisms are the key point to wireless cellular networks. In this paper, we present an adaptive algorithm for dynamic channel allocation scheme with guard channels and also with handoff calls waiting queue ensuring that handoff calls take priority over new calls. Our goal is to find better tradeoff between handoffs and new calls blocking probabilities in order to achieve more efficient channel utilization. Simpy is a Python based discrete event simulation system. We use Simpy to build our simulation models to get analytical data.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1156-1170
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• 2019

In recent years, the problem of data drifted of the smart grid due to manual operation has been widely studied by researchers in the related domain areas. It has become an important research topic to effectively and reliably find the reasonable data needed in the Supervisory Control and Data Acquisition (SCADA) system has become an important research topic. This paper analyzes the data composition of the smart grid, and explains the power model in two smart grid applications, followed by an analysis on the application of each parameter in density-based spatial clustering of applications with noise (DBSCAN) algorithm. Then a comparison is carried out for the processing effects of the boxplot method, probability weight analysis method and DBSCAN clustering algorithm on the big data driven power grid. According to the comparison results, the performance of the DBSCAN algorithm outperforming other methods in processing effect. The experimental verification shows that the DBSCAN clustering algorithm can effectively screen the power grid data, thereby significantly improving the accuracy and reliability of the calculation result of the main grid's theoretical line loss.

• Structural Engineering and Mechanics
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• v.73 no.3
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• pp.331-337
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• 2020

This paper proposes a new approximate analytical solution for highly nonlinear vibration of mechanical systems called Hamiltonian Approach (HA) that can be widely use for structural health monitoring systems. The complete procedure of the HA approach is studied, and the precise application of the presented approach is surveyed by two familiar nonlinear partial differential problems. The nonlinear frequency of the considered systems is obtained. The results of the HA are verified with the numerical solution using Runge-Kutta's [RK] algorithm. It is established the only one iteration of the HA leads us to the high accurateness of the solution.

• Proceedings of the KSRS Conference
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• v.1
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• pp.479-482
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• 2006

The absorption coefficient and backscattering properties of phytoplankton were calculated from the Mie theory. Given a simple case that phytoplankton and mineral particles are the only constitutions in seawater, the reflectance $b_b({\lambda})/[a({\lambda})+b_b({\lambda})]$was analyzed. Then the chlorophyll concentrations were estimated from remote sensing OC2 algorithm. The results show that reflectance in short wavelength region is more sensitive to the Chl variation; High mineral concentrations in seawater have significant influence on the reflectance spectrum; the existence of high mineral concentration may result in the mistake in chlorophyll estimation from OC2 algorithm.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1315-1325
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• 2019

Aiming at the negative sequence and harmonic problems in the operation of railway static power conditioners, an optimization compensation strategy for negative sequence and harmonics is studied in this paper. First, the hybrid RPC topology and compensation principle are analyzed to obtain different compensation zone states and current capacities. Second, in order to optimize the RPC capacity configuration, the minimum RPC compensation capacity is calculated according to constraint conditions, and the optimal compensation coefficient and compensation angle are obtained. In addition, the voltage unbalance ${\varepsilon}_U$ and power factor requirements are satisfied. A PSO (Particle Swarm Optimization) algorithm is used to calculate the three indexes for minimum compensating energy. The proposed method can precisely calculate the optimal compensation capacity in real time. Finally, MATLAB simulations and an experimental platform verify the effectiveness and economics of the proposed algorithm.

• ETRI Journal
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• v.44 no.5
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• pp.769-779
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• 2022

Spectral clustering has become a typical and efficient clustering method used in a variety of applications. The critical step of spectral clustering is the similarity measurement, which largely determines the performance of the spectral clustering method. In this paper, we propose a novel spectral clustering algorithm based on the local similarity measure of shared neighbors. This similarity measurement exploits the local density information between data points based on the weight of the shared neighbors in a directed k-nearest neighbor graph with only one parameter k, that is, the number of nearest neighbors. Numerical experiments on synthetic and real-world datasets demonstrate that our proposed algorithm outperforms other existing spectral clustering algorithms in terms of the clustering performance measured via the normalized mutual information, clustering accuracy, and F-measure. As an example, the proposed method can provide an improvement of 15.82% in the clustering performance for the Soybean dataset.