• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4387-4404
• /
• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• Journal of Advanced Marine Engineering and Technology
• /
• v.34 no.8
• /
• pp.1222-1229
• /
• 2010

Compared to conventional high resolution acoustic profiling, ultra high resolution shallow acoustic profiling using parametric echo sounder is limited in penetration, yet it provides resolution suitable for detailed seabed investigation in the shallow waters. The parametric sub-bottom profiler system provides not only the exact determination of water depth, but also the detailed information about sediment layers and sub-bottom structures. Possible applications include dredging project, search of buried pipeline, ship wrecks, and other artificial objects through the detailed mapping of thickness and structure of the upper sedimentary layers. In this study, contaminated sediments were discriminated by the correlation of ultra high resolution profiles with geologic data. In addition, the burial depth of the submarine cable was measured by the interpretation of acoustic anomalies in the profiles.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.5
• /
• pp.1829-1831
• /
• 2012

Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

• Journal of Korean Society of Steel Construction
• /
• v.19 no.3
• /
• pp.335-344
• /
• 2007

The steel-concrete composite column (i.e., the SC composite column) supports large-gravity loads and simplifies the installation and removal of the work in pouring the concrete. The column takes advantage of the in-plant prefabrication of steel, the speed of erection of a steel structure, and the fire resistance of steel. This paper presents the results of a parametric study using heat transfer analysis and a P-M interaction curve, and compares these results with the experimental results to check the accuracy of the proposed parametric studies. The parametric studies, such as the study of the concrete ratio of an area and the fire protection thickness, provide information on the fire resistance of SC composite columns.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.5
• /
• pp.162-166
• /
• 2009

In this paper, we propose a novel approach of an acoustic echo cancellation (AEC) algorithm which is differently adopted in the relevant period condition by the suppression parameter of a parametric wiener filter (PWF). The PWF uses the suppression parameter to compensate uncertainty of acoustic echo signal estimation. The existing PWF method using the fixed suppression parameter derives the distortion of the near-end signal at the double-talk. To solve this problem, the boundary condition is devised using decision of the double-talk detection (DTD) algorithm and voice activity detector (VAD). The boundary condition makes it possible to treat differently depending on the case of the single-talk and double-talk. According to the experimental results, the proposed approach is found to be effective for acoustic echo cancellation using the boundary condition.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.6
• /
• pp.341-348
• /
• 2019

The purpose of this study is to model and analyze retractable large spatial structures by applying parametric modeling techniques. The modeling of wind loads in the analysis of typical structures including curved surfaces can be error-prone, and the processing time increases dramatically when there are many types of variables. However, the method based on StrAuto that was developed in previous research, facilitates the efficacious assignment of wind loads to structures and the rapid arrival of conclusions. As a result, it is possible to compare alternatives with various loads, including wind loads, to determine an optimal alternative much faster than the existing process. Further, it is almost impossible to directly input the wind load by calculating the area of an irregularly curved surface. However, the proposed method automatically assigns the wind load, which allows for automatic optimization in a structural analysis system. The approach was applied and optimized using several models, and the results are presented.

• Journal of the Korean Society of Systems Engineering
• /
• v.3 no.1
• /
• pp.41-48
• /
• 2007

This paper presents a design methodology for developing a new push scooter. A case study is clone with effective planning processes to ensure the product quality under the different phases of a product design process. Parametric model based design process simulation and optimization is implemented by using ANSYS application tool. The relationship matrix and decision matrix are drawn by using several methods. The simulation results for deterministic design and robust design are compared. This entire design process phase can support the design and quality improvements for a new product development.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.221-227
• /
• 2014

In this paper, we propose a synthesis method that can effectively suppress the ambience which affects tonal components in the PS decoder. Ambience component was obtained by using decorrelation filter and the weighting of the ambience in the decoder was determined through IC parameter. However, since the parameters are extracted in the sub-band domain, a low IC value could be analyzed even if the tonal component is dominant. The quality of the output signal may be degraded. To prevent this problem, the tonality was measured in the downmixed signal and the weighting of the ambience components were adjusted appropriately according to the measured tonality index. The performance of the proposed method was evaluated by simulations. Furthermore, the subjective test was performed and the results confirmed that the proposed method offers improved quality.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.4
• /
• pp.86-97
• /
• 2011

This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.

• Journal of Internet Computing and Services
• /
• v.13 no.5
• /
• pp.1-8
• /
• 2012

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.