• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.12
• /
• pp.3061-3080
• /
• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.6
• /
• pp.1023-1041
• /
• 2010

In cognitive radio networks, cooperative spectrum sensing schemes are proposed to improve the performance of detecting licensees by secondary users. Commonly, the cooperative sensing can be realized by means of hard decision fusion (HDF) or soft decision fusion (SDF) schemes. The SDF schemes are superior to the HDF ones in terms of the detection performance whereas the HDF schemes are outperforming the SDF ones when the traffic overhead is taken into account. In this paper, a hybrid SFD-HDF cluster-based approach is developed to jointly exploit the advantages of SFD and HDF schemes. Different SDF schemes have been proposed and compared within a given cluster whereas the OR-rule base HDF scheme is applied to combine the decisions reported by cluster headers to a common receiver or base station. The computer simulations show promising results as the performance of the proposed scenario of hybridizing soft and hard fusion schemes is significantly outperforming other different combinations of conventional SDF and HDF schemes while it noticeably reduces the network traffic overhead.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.879-888
• /
• 2005

Fashion is hard to expect owing to the rapid change in accordance with consumer taste and environment, and has a tendency toward variety and individuality. Especially street fashion of 21st century is not being regarded as one of the subcultures but is playing an important role as a fountainhead of fashion trend. Therefore, Searching and analyzing street fashions helps us to understand the popular fashions of the next season and also it is important in understanding the consumer fashion sense and commercial area. So, we need to understand fashion styles quantitatively and qualitatively by providing visual data and dividing images. There are many kinds of data in street fashion information. The purpose of this study is to design and implementation for street fashion information analysis system using data fusion. We can show visual information of customer's viewpoint because the system can analyze the fused data for image data and survey data.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.4
• /
• pp.53-58
• /
• 2022

Shape changes of hard mask play a key role in the aspect ratio dependent etch (ARDE). For etch process using high density and energy ions, deformation of hard mask shape becomes more severe, and high aspect ratio (HAR) etch profile is distorted. In this study, polygonal geometric model for shape-deformation of amorphous carbon layered hard mask is suggested to control etch profile during the process. Mask shape is modeled with polygonal geometry consisting of trapezoids and rectangles, and it provides dynamic information about angles of facets and etched width and height of remained mask shape, providing important features for real-time HAR etch profiling.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.11
• /
• pp.47-56
• /
• 2010

In navigation, officers receive data about inside and outside of ship from several devices(ex, GPS / AIS / ECDIS / ARPA Radar / etc) in bridge, and use it to recognize and predict safety situations. However, observation work of a officer is still hard for a torrent of data from several devices, and the problem of inconsistent data among the devices. In previous research, we presented the conceptual model of Intelligent Navigation Safety Information System based on information fusion, and showed the example of the conceptual model using CF (Certainty Factor) expert system to solve this problem. The information fusion technology needs various reasoning skills, and CF expert system is not enough to express ambiguous or indefinite factors. In this paper, we propose the concept of an intelligent navigation information fusion using fuzzy expert system to describe the ambiguous factors, and show the validity of applying fuzzy expert system to the Navigation Safety Information System through the design and implementation of the proposed concept.

• Korean Journal of Remote Sensing
• /
• v.22 no.1
• /
• pp.75-85
• /
• 2006

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2002.10a
• /
• pp.219-223
• /
• 2002

Many data fusion techniques have been widely studied, but some methods were hard to apply due to complicated theoretical backgrounds and complexed steps. In this study, we tried to compare the wavelet transform, which has been accepted as the best method in terms of spectral distortion, and other three handy methods, which are available in most commercial software. Four clipped test areas were selected for different spectral information. There is, however, no huge improvement in clipped images except water areas. Overall the wavelet transform are superior in most areas, but the multiplicative method relatively gives good correlation.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.604-615
• /
• 2019

Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

• Journal of Communications and Networks
• /
• v.14 no.5
• /
• pp.471-480
• /
• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.792-793
• /
• 2016

Recent studies on a fusion of health care system and the information and communication technology of wearable is being developed Anytime and anywhere without being constrained to measure the biological information of the user. However existing wearable monitors the measured biological information. If the user is hard to deal with for the event of dangerous situations. In this paper, it proposes a system that identifies the status of a user to correct the problem it utilizes sensors and algorithms to measure the biological information. This enables the user will be able to respond quickly to dangerous situations. In the event of a dangerous situation, such as falling or stumbling sends an emergency alert to a designated guardian.