• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2908-2924
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• 2019

Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is widely applied in wireless communication by virtue of its excellent properties in data transmission rate and transmission accuracy. However, as a major drawback of MIMO-OFDM systems, the high peak-to-average power ratio (PAPR) complicates the design of the power amplifier at the receiver end. Some available PAPR reduction methods such as selective mapping (SLM) suffer from high computational complexity. In this paper, a low-complexity SLM method based on active constellation extension (ACE) and joint space-time selective mapping (AST-SLM) for reducing PAPR in Alamouti STBC MIMO-OFDM systems is proposed. In SLM scheme, two IFFT operations are required for obtaining each transmission sequence pair, and the selected phase vector is transmitted as side information(SI). However, in the proposed AST-SLM method, only a few IFFT operations are required for generating all the transmission sequence pairs. The complexity of AST-SLM is at least 86% less than SLM. In addition, the SI needed in AST-SLM is at least 92.1% less than SLM by using the presented blind detection scheme to estimate SI. We show, analytically and with simulations, that AST-SLM can achieve significant performance of PAPR reduction and close performance of bit error rate (BER) compared to SLM scheme.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.4
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• pp.269-275
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• 2017

$NO_X$ reducing technique such as LNT, LNC, and selective catalytic reduction (SCR) have been developed and applied, especially on heavy-duty vehicles. However, it is expected that $NO_X$ reduction techniques will also be applied to diesel passenger vehicles. The urea-SCR system is receiving attention as the most effective $NO_X$ reduction technology without a fuel penalty. Thus, many advanced countries are developing this technology. The urea-SCR system sprays an aqueous urea solution that separates $NO_X$ into $N_2$ and $H_2O$, which are harmless and emitted into the atmosphere. The urea injected in front of the SCR catalyst should be changed to 100％ $NH_3$, which is required for $NO_X$ reduction in the SCR system to maximize the reduction efficiency. The purpose of this study was to determine the basic data for the urea-SCR system to maximize the $NO_X$ reduction efficiency by understanding the $NO_X$ reduction characteristics in a real passenger vehicle to comply with the post EURO-6 emission regulation.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.605-615
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• 2017

Efficient simultaneous reduction conditions for $NO_x$ and $NH_3$-slip was investigated in SCR (Selective Catalytic Reduction) process with load variation by applying dual catalysts (SCR catalyst, $NH_3$ decomposition catalyst) system. $N_2O$ formation characteristics were analyzed to look into possible undesirable reaction pathways. In the experiments of catalyst characteristics, various operational variables were tested for the combined catalytic system, such as $NH_3/NO_x$ ratio, temperature, oxygen concentration and $H_2O$. The reaction characteristics of $NO_x$, $NH_3$ and $N_2O$ were analyzed and optimal conditions could be evaluated for the combustion facility with varied load. In terms of $NO_x/NH_3$ simultaneous reduction and $N_2O$ formation suppression, optimal condition was considered NSR 1.2 and temperature $300^{\circ}C$. At this operational condition, $NO_x$ conversion was 98%, $NH_3$ reduction efficiency was 95%, generated $N_2O$ concentration 9.5 ppm with inlet $NO_x$ concentration of 100 ppm. In $NH_3-SCR$ process with $NH_3$ decomposition catalyst, $NO_x$ and $NH_3$ can be considered to be reduced simultaneously at limited conditions. The results of this study may be utilized as basic data at facilities requiring simultaneous $NO_x$ and $NH_3$ reduction for facilities with load variation.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2953-2957
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• 2016

Background: Breast Cancer (BCa) is the most common malignant tumour in Mexican women. In BCa, several studies have linked ${\beta}2-adrenergic$ receptor activation with increased tumour growth and progression as related with Epinephrine-NorEpinephrine (E-NE) stimulation. The aim of this study was to describe Beta-Blocker (BB) treatment related with reduction of the risk of metastasis in Mexican patients with BCa. Materials and Methods: We collected data of 120 patients seen at the High-Specialty Naval General Hospital in Mexico City (HOSGENAES), all of these with a histopathological diagnosis of BCa. Four groups of patients were divided as follows: without Systemic Arterial Hypertension (SAH); with SAH treatment with non-selective BB; with SAH treatment with selective BB, and with SAH treatment with other antihypertensive drugs. Chi-square, Mantel-Haenszel, Student t, and ANOVA tests were performed for data analysis. Results: On average, patients were $54.8{\pm}11.8$ years of age. Risk factors such as smoking and consuming alcohol exhibited a frequency of 33 and 36.5% respectively. Clinical stages III- IV were found in 50% of patients, while, 30% of patients had arterial hypertension (n=29 and N=96, respectively) and 17.5% used BB. One hundred percent of patients with arterial hypertension treated with BB for ${\beta}1$ - and ${\beta}2$ -adrenergic-receptors did not present metastasis globally, but patients treated with ${\beta}1$ BB presented 30% of metastasis while patients treated with no BB or without SAH had around 70% of metastasis. Conclusions: In Mexican patients with BCa and SAH treated with non-selective (${\beta}1$- and ${\beta}2-adrenergic$ receptors) BB, a decrease in the risk for metastasis was observed at the time of diagnosis.

• Journal of Fashion Business
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• v.9 no.3
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• pp.22-36
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• 2005

This research is to classify psychological risk perceptions in purchases process at counterfeit at fashion luxury brands, into a risk perception on purchase activity itself and a risk perception on the post-purchase situation, and to analyze types and characteristics at risk reduction behaviors to reduce each risk perception. In this research a qualitative method was employed, and research-related data were collected and analyzed through in-depth interviews. Results were shown that risk reduction behaviors at psychological risk perception on purchase activity itself included rationalization of purchase, accompanied purchase, reduction and discontinuance of purchase, and that risk reduction behaviors of psychological risk perception on the post-purchase situation included information search, establishment of selection criteria, establishment of marginal limit, selective purchase, planned and compared purchase, and reduction and discontinuance of purchase. Previous researches suggested brand loyalty, selection of famous brands, utilization of information agents by marketers, pre-purchase usage and guaranteed purchase, but these risk reduction methods were not utilized, this probably being interpreted as a result of characteristics of counterfeit. In addition, risk reduction behavior of one type tended to reduce risk perception of several other types, and risk reduction behaviors of various types were utilized to reduce a certain type's risk perception. Not only types of risk perception but also levels of risk perception appeared to have exerted influence to risk reduction behaviors.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.818-826
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• 2004

The spray-induced mixing characteristics and thermal decomposition of aqueous urea solution into ammonia have been studied to design optimum sizes and geometries of the mixing chamber in SCR(Selective Catalytic Reduction) system. The cold flow tests about the urea-injection nozzle were performed to clarify the parameters of spray mixing characteristics such as mean diameter and velocity of drops and spray width determined from the interactions between incoming air and injected drops. Discrete particle model in Fluent code was adopted to simulate spray-induced mixing process and the experimental results on the spray characteristics were used as input data of numerical calculations. The simulation results on the spray-induced mixing were verified by comparing the spray width extracted from the digital images with the simulated Particle tracks of injected drops. The single kinetic model was adopted to predict thermal decomposition of urea solution into ammonia and solved simultaneously along with the verified spray model. The hot air generator was designed to match the flow rate and temperature of the exhaust gas of the real engines The measured ammonia productions in the hot air generator were compared with the numerical predictions and the comparison results showed good agreements. Finally, we concluded that the design capabilities for sizing optimum mixing chamber were established.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.70-73
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• 2007

Many methods have been developed to overcome the PAPR(peak-to-average power ratio) problem. Selective mapping(SLM) partial transmit sequence(PTS), subblock phase weighting(SPW) and gradient descent(GD) are used widely to reduce the PAPR. In this paper, we present a effective PAPR reduction method, decrease the calculation through Radix-2 DIF IFFT procedure and GD method. and can transmit selecting data sequence that satisfy threshold value as one part of proposed method, in case satisfy fixed threshold value, or transmit selecting data sequence with the lower papr operating remained part for performance improvement.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.247-262
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• 2024

In this paper, we explore nonlinear sufficient dimension reduction (SDR) methods, with a primary focus on establishing a foundational framework that integrates various nonlinear SDR methods. We illustrate the generalized sliced inverse regression (GSIR) and the generalized sliced average variance estimation (GSAVE) which are fitted by the framework. Further, we delve into nonlinear extensions of inverse moments through the kernel trick, specifically examining the kernel sliced inverse regression (KSIR) and kernel canonical correlation analysis (KCCA), and explore their relationships within the established framework. We also briefly explain the nonlinear SDR for functional data. In addition, we present practical aspects such as algorithmic implementations. This paper concludes with remarks on the dimensionality problem of the target function class.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.889-900
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• 2006

Even though sensor networks are different in user requests and data characteristics depending on each application area, the existing researches on stream data transmission problem focus on the performance improvement of their methods rather than considering the original characteristic of stream data. In this paper, we introduce a hierarchical or distributed sensor network architecture and data model, and then evaluate the multivariate data reduction methods suitable for user requirements and data features so as to apply reduction methods alternatively. To assess the relative performance of the proposed multivariate data reduction methods, we used the conventional techniques, such as Wavelet, HCL(Hierarchical Clustering), Sampling and SVD (Singular Value Decomposition) as well as the experimental data sets, such as multivariate time series, synthetic data and robot execution failure data. The experimental results shows that SVD and Sampling method are superior to Wavelet and HCL ia respect to the relative error ratio and execution time. Especially, since relative error ratio of each data reduction method is different according to data characteristic, it shows a good performance using the selective data reduction method for the experimental data set. The findings reported in this paper can serve as a useful guideline for sensor network application design and construction including multivariate stream data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.340-343
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• 2007

OFDM (Orthogonal Frequency Division Multiplexing) system is robust to frequency selective fading and narrowband interference in high-speed data communications. However, an OFDM signal consists of a number of independently modulated subcarriers, which can give a large PAPR (peak-to-Average Power Ratio) when added up coherently. In this paper, we propose a new PAPR reduction method using Adaptive Sine Soft Clipping (ASS Clipping) to solve the PAPR problem. The proposed method reduce the PAPR and out-of-band spectrum by cutting down high frequency components. From computer simulation results, we analyze the PSD (Power Spectral Density) and BER (Bit Error Rate) performance as well as PAPR reduction performance when the ASS Clipping method is applied to OFDM system.