• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.449-468
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• 2023

This paper deals in the study of the estimation of the parameters of Erlang distribution based on rank set sampling and some of its modifications. Here we considered Maximum Likelihood (ML) and the Bayesian technique to estimate the shape and scale parameter of Erlang distribution based on RSS and its some modifications such as ERSS, MRSS, and MRSSu. The derivation for unknown parameters of Erlang distribution is well presented using normal approximation to the asymptotic distribution of ML estimators. But due to the complexity involves in the integral, the Bayes estimator of unknown parameters is obtained using MCMC method. Further, we compared the MSE of estimation in different sampling schemes with different set sizes and cycle size. A real-life data application is also given to illustrate the efficiency of the proposed scheme.

• The KIPS Transactions:PartA
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• v.11A no.6
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• pp.419-424
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• 2004

Mobile Internet using mobile devices provides Portability to users and is Spreading throughout out lives. But Practical use of the mobile Internet is insufficient due to it's fundamental limitations. Especially, mobile resources are not sufficient because they are not closely connected under current mobile Internet services which are provided with pre-designed structure. For these reasons it will take a lot more time and effort for mobile Internet to grow as a popular service. In this paper, we are focusing to overcome the local limitation and to enhance the 'Sharing of Mobile Resources' by expanding mutual connectivity between resource objects scattered over the mobile Internet environment. To archive this, we propose the MRSS(Mobile Resources Sharing System). MRSS automatically converts single request from user to multiple instructions based on 'Context-Awareness' to search for proper information. Using MRSS, we can expect 'Mobile Ubiquitous Computing' environment which users can reach to information anywhere, anytime.

• Environmental Engineering Research
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• v.20 no.3
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• pp.268-276
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• 2015

Solid waste production increases due to population and consumption increments. Landfill is the ultimate destination for all kinds of municipal solid waste; and is the most convenient waste disposal method in developing countries. To minimize investment and operational costs and society's opposition towards locating landfills nearby, proper landfill sizing and siting are essential. In this study, solid waste forecasting using Autoregressive Integrating Moving Average (ARIMA) was integrated with government future plans and waste composition to estimate the required landfill area for the state of Selangor, Malaysia. Landfill siting criteria were then prioritized based on expert's preferences. To minimize ambiguity and the uncertainty of the criteria prioritizing process, the expert's preferences were treated using integrated Median Ranked Sample Set (MRSS) and Analytic Hierarchy Process (AHP) models. The results show that the required landfill area is 342 hectares and the environmental criteria are the most important; with a priority equal to 48%.

• Journal of Veterinary Science
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• v.21 no.1
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• pp.11.1-11.7
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• 2020

The increase in canine skin and soft tissue infections, such as pyoderma and otitis, caused by Staphylococcus schleiferi strains, is of significant zoonotic concern. In this study, we report the first complete genome sequence for a methicillin-resistant clinical isolate of S. schleiferi (MRSS) designated as SS4, obtained from a dog with otitis externa, in Korea. The genome of SS4 strain was of 2,539,409 bp and presented high G+C content ratio (35.90%) with no plasmid. Comparative analysis of SS4 genome revealed that it is closely related to 2142-05 and 5909-02 strains isolated from the canine skin infections in the USA.

• Journal of Magnetics
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• v.19 no.4
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• pp.345-348
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• 2014

Magnetorheological suspensions (MRSs) are smart materials that have the potential to revolutionize several industrial sectors because of their special rheological behaviors. In this paper, MRS, based on carbonyl iron (CI) microparticles that were dispersed in silicone oil with oleic acid, were prepared. We showed that the electroconductibility of MRS was significantly influenced by the intensity of the external magnetic field that was applied. The resistance value can vary from infinite to below $300{\Omega}$ after applying an external magnetic field. The results indicated that this MRS had the property of magnetic-field-tuned insulator to conductor transition. This system has potential applications in controllable MRS electrical devices.

• Broadcasting and Media Magazine
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• v.11 no.1
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• pp.68-77
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• 2006

The Cognitive Radio (CR) technology is a promising solution for exploiting the limited spectrum resources and providing flexibility of spectrum usage. Future interactive broadcasting service can be realized by utilizing CR concept, since the up-link return channel can be found by the spectrum sensing method, which is core functional block of the CR system. In this paper, the spectrum sensing technologies of CR system is presented. First the system architecture of the CR with spectrum sensing block is presented. The suggested spectrum sensing technique consists of the coarse and the fine spectrum sensing. The coarse spectrum sensing technique adopted the wavelet transform to provide the multi-resolution sensing feature - Multi-Resolution Spectrum Sensing (MRSS). The fine spectrum sensing technique uses the beneficial properties of the autocorrelation function Analog Auto-Correlation (AAC). The simulation results for the proposed sensing technologies are presented for various incumbent signals.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.87-99
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• 2006

The Median Resolution Sensors (MRSs) for land observation such as Landsat-ETM+ and SPOT-HRV are more effective than Ocean Color Sensors (OCSs) for studying of detailed ecological and biogeochemical components of the coastal waters. In this study, we developed suspended sediment algorithm for Landsat TM/ETM+ by considering the spectral response curve of each band. To estimate suspended sediment concentration (SS) from satellite image data, there are two difference types of algorithms, that are derived for enhancing the accuracy of SS from Landsat imagery. Both empirical and remote sensing reflectance model (hereafter referred to as $R_{rs}$ model) are used here. This study tried to compare two algorithm, and verified using in situ SS data. It was found that the empirical SS algorithm using band 2 produced the best result. $R_{rs}$ model-based SS algorithm estimated higher values than empirical SS algorithm. In this study we used $R_{rs}$ model developed by Ahn (2000) focused on the Mediterranean coastal area. That's owing to the difference of oceanic characteristics between Mediterranean and Korean coastal area. In the future we will improve that $R_{rs}$ model for the Korean coastal area, then the result will be advanced.