• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3359-3366
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• 2023

In this study, a spiking cortical model (SCM) based n-g discrimination method is proposed. The SCM-based algorithm is compared with three other methods, namely: (i) the pulse-coupled neural network (PCNN), (ii) the charge comparison, and (iii) the zero-crossing. The objective evaluation criteria used for the comparison are the FoM-value and the time consumption of discrimination. Experimental results demonstrated that our proposed method outperforms the other methods significantly with the highest FoM-value. Specifically, the proposed method exhibits a 34.81% improvement compared with the PCNN, a 50.29% improvement compared with the charge comparison, and a 110.02% improvement compared with the zero-crossing. Additionally, the proposed method features the second-fastest discrimination time, where it is 75.67% faster than the PCNN, 70.65% faster than the charge comparison and 38.4% slower than the zero-crossing. Our study also discusses the role and change pattern of each parameter of the SCM to guide the selection process. It concludes that the SCM's outstanding ability to recognize the dynamic information in the pulse signal, improved accuracy when compared to the PCNN, and better computational complexity enables the SCM to exhibit excellent n-γ discrimination performance while consuming less time.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.897-908
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• 2024

Evaluating the adequacy of facility safety inspection and diagnosis services performed by private enterprises is a time-consuming and administratively complex process. This study aims to analyze the determinants that could influence the rating of these safety inspection and diagnosis services using data analytics approach. Through a comparative analysis of several machine learning algorithms suitable for multi-class classification, we selected the model with the best performance (Random Forest) and identified the main determinants using the permutation importance technique. Among the variables examined, "contract value," "days of service performed" and "adherence to fair market value" were found to be strongly correlated with the rating assessments. Furthermore, we discovered that the skills and expertise of service performing personnel significantly impacted the rating. The results of this study can contribute to the enhancement of the current post-evaluation administrative processes and offer valuable insights into rating assessments by incorporating previously unexplored variables pertaining to both service providers and the services itself.

• Wind and Structures
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• v.26 no.6
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• pp.383-395
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• 2018

An accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2458-2482
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• 2023

Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1042-1049
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• 2007

Recently, a theoretically-sound design approach, using an elastic multilayer model, is attempted in trackbed designs for the construction of high speed railways and new lines of conventional railways. In the elastic multilayer model, the stress-dependent resilient modulus($E_R$) is an important input parameter, that is, reflects substructure performance under repeated traffic loading. However, the evaluation method for resilient modulus using repeated loading triaxial test is not fully developed for practical purpose, because of costly equipment and the significantly fluctuated values depending on the testing equipment and laboratory personnel. In this study, the paper will present an indirect method to estimate the resilient modulus using dynamic properties. The resilient modulus of crushed stone, which is the typical material of sub-ballast, was calculated with the measured dynamic properties and the range of stress level of the sub-ballast, and approximated with the power model combined with bulk and deviatoric stresses. The resilient modulus of coarse grained material decreases with increasing deviatoric stress at a confining pressure, and increases with increasing bulk stress. Sandy soil(SM classified from Unified Soil Classification System) of subgrade was also evaluated and best fitted with the power model of deviatoric stress only.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.346-354
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• 2020

Nowadays, it is required to apply low observable technology to weapon systems in operation or under development. Radar Cross Section(RCS) is a measure of the scattered power in an given direction when a target is illuminated by an incident wave and used as a parameter to estimate the low observable performance of weapon system. RCS of a target can be calculated by various numerical methods. However, measurement is also needed to estimate RCS of a complex target because it is difficult to estimate theoretically. To acquire reliable measurement results, an analysis of measurement uncertainty is essential. In this paper, error components and uncertainties of near-field RCS measurement system which was constructed in ASTEC(Aerospace System Test & Evaluation Center) were analyzed based on the IEEE recommended practice for radar cross-section test procedures(IEEE Std. 1502-2007) which describes the uncertainty of RCS measurement and unique error components of this near-field measurement system were also identified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.37-41
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• 2018

In this paper, we evaluate the power consumption of IEEE802.15.4e TSCH which uses the specific link scheduling scheme proposed in reference[1]. And we also compares it with the power consumption of conventional single channel IEEE802.15.4. The power consumption of IEEE802.15.4e TSCH is smaller than the conventional one under the any conditions of traffic. The reasons can be explained as the followings. Firstly, TSCH does not have backoff time because of using the collision free link scheduling. Secondly, there is the timing difference of MAC offset parameter between TSCH and conventional IEEE802.15.4 Lastly, the devices in TSCH mode sleep during the time slots which are not assigned to itself.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.617-624
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• 2014

Smart phone usage has increased exponentially and open source based Android OS occupy significant market share. However, various malicious applications that use the characteristic of Android threaten users. In this paper, we construct an efficient malicious application detector by using the principle component analysis and the incremental k nearest neighbor algorithm, which consider an required permission, of Android applications. The cross validation is exploited in order to find a critical parameter of the algorithm. For the performance evaluation of our approach, we simulate a real data set of Contagio Mobile.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.48-58
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• 1998

In this paper, we proposed a new algorithm using characteristics of th ereconstructed phase trajectory by topological mapping developed for a real-tiem detection of the QRS complexes of ECG signals. Using fill-factor algorithm and mutual information algorithm which are in genral used to find out the chaotic characteristics of sampled signals, we inferred the proper mapping parameter, time delay, in ECG signals and investigated QRS detection rates with varying time delay in QRS complex detection. And we compared experimental time dealy with the theoretical one. As a result, it shows that the experimental time dealy which is proper in topological mapping from ECG signals is 20ms and theoretical time delays of fill-factor algorithm and mutual information algorithm are 20.+-.0.76ms and 28.+-.3.51ms, respectively. From these results, we could easily infer that the fill-factor algorithm in topological mapping from one-dimensional sampled ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper time delay. Also with the proposed algorithm which is very simple and robust to low-frequency noise as like baseline wandering, we could detect QRS complex in real-time by simplifying preprocessing stages. For the evaluation, we implemented the proposed algorithm in C-language and applied the MIT/BIH arrhythmia database of 48 patients. The proposed algorithm provides a good performance, a 99.58% detection rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.1
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• pp.85-100
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• 1991

In the discussion of digital mobile communication systems the speech coder based on the high quality low bit rate is an essential part of topics to overcome the limited availability of radio spectrum, which will enhance the communication services. In this paper we present the implementation and performance evaluation of 13kbps RPE LTP speech coder. An implementation of a real time full duplex coder with 75% of DSP loading rate using a single DSP chip has been shown, and also the fixed point simulations for H/W implementation has been performed. Finally, analysis result for relative bit importance of each transmitting parameter has been shown for channel coding.