• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.11-23
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• 2014

Wireless Mesh Network(WMN) has drawn much attention due to easy deployment and good scalability. Recently, major power utilities have been focusing on R&D to apply WMN technology in Smart Grid Network. Smart Grid is an intelligent electrical power network that can maximize energy efficiency through bidirectional communication between utility providers and customers with ICT(Information Communication Technology). It is necessary to guarantee QoS of some important data in Smart Grid system such as real-time data delivery. In this paper, we suggest QoS enhancement method for WMN based Smart Grid system using IEEE 802.11s. We analyze Smart Grid Application characteristics and apply IEEE 802.11s WMN scheme for Smart Grid in domestic power communication system. Performance evaluation is progressed using NS-2 simulator implementing IEEE 802.11s. The simulation results show that the QoS enhancement scheme can guarantee stable bandwidth irrespective of traffic condition due to IEEE 802.11s reservation mechanism.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.312-321
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• 2018

The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

• Journal of IKEEE
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• v.18 no.4
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• pp.471-477
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• 2014

In this paper, we propose a low-cost license plate recognition system based on smart cam system using Android. The proposed system consists of a portable device and server. Potable device Hardware consists of ARM Cortex-A9 (S5PV210) processor control unit, a power supply device, wired and wireless communication, input/output unit. We develope Linux kernel and dedicated device driver for WiFi module and camera. The license plate recognition algorithm is consisted of setting candidate plates areas with canny edge detector, extracting license plate number with Labeling, recognizing with template matching, etc. The number that is recognized by the device is transmitted to the remote server via the user mobile phone, and the server re-transfer the vehicle information in the database to the portable device. To verify the utility of the proposed system, user photographs the license plate of any vehicle in the natural environment. Confirming the recognition result, the recognition rate was 95%. The proposed system was suitable for low cost portable license plate recognition device, it enabled the stability of the system when used long time by using the Android operating system.

• Journal of IKEEE
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• v.22 no.3
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• pp.638-644
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• 2018

In this paper, we develop a measurement system that uses 3D Scintillator and NaI(TI) Detector to 3-dimensionally identify the location of multiple radiation sources in moving vehicle loads. The radiation measurement system consists of radiation measurement (plastic scintillator), 2-channel Pulse Counter Board, nuclide analysis (NaI(TI) detector) and 1 channel MCA Board. The source locator algorithm calculates the coordinate value of the ratio of the CPS value($1/r^2$) of the source according to the angle(${\theta}$) in inverse proportion to the square of the distance(X, Y) through the SVM classification. The coordinate values are input every predetermined period of the spectrum, and after analyzing the spectrum per unit cycle, the position of the nuclide at the time is calculated by determining whether or not the nuclide is present in the remaining part except for the background area. As a result of the position discrimination test, the error within the international standard of ${\pm}1m$ was shown. Thus, the utility of the proposed system has been demonstrated.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.55-60
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• 2007

In high field (> 3 T) MR imaging, the magnetic field inhomogeneity in the target object increases due to the nonuniform electro-magnetic characteristics of the relatively high RF frequency. Especially in the body imaging, the effect causes more serious problems resulting in locally high SAR(Specific Absorption Ratio). In this paper, we propose an optimized parallel-transmission RF coil and show the utility of the coil by FDTD simulations to overcome the unwanted effects. Three types of TX coil elements are tested to maximize the efficiency and their driving patterns(amplitude and phase) optimized to have adequate field homogeneity, proper SAR level, and sufficient field strength. For the proposed coil element of $25cm{\times}8cm$ loop structure with 12 channels for a 3.0 T body coil, the field non-uniformity of more than 70% without optimization was reduced to about 26 % after the optimization of driving patterns. The experimental as well as simulation results show that the proposed parallel driving scheme is clinically useful for (ultra) high field MRI.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.203-213
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• 2024

This study delves into the mechanical properties of fiber-reinforced cement composites(FRCC) concerning the dispersion method of multi-walled carbon nanotubes(MWCNTs). MWCNTs find utility in industrial applications, particularly in magnetic sensing and crack detection, owing to their diverse properties including heat resistance and chemical stability. However, current research endeavors are increasingly directed towards leveraging the electrical properties of MWCNTs for self-sensing and smart sensor development. Notably, achieving uniform dispersion of MWCNTs poses a challenge due to variations in researchers' skills and equipment, with excessive dispersion potentially leading to deterioration in mechanical performance. To address these challenges, this study employs ultrasonic dispersion for a defined duration along with PCE surfactant, known for its efficacy in dispersion. Test specimens of FRCC are prepared and subjected to strength, drawing, and direct tensile tests to evaluate their mechanical properties. Additionally, the influence of MWCNT dispersion efficiency on the enhancement of FRCC mechanical performance is scrutinized across different dispersion methods.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.5
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• pp.459-467
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• 2009

Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.