Jamming Effect Analysis of Two Chinese GNSS BeiDou-II Civil Signals

Threats of electronic warfare, especially to global positioning systems (GPSs), have been rapidly increasing. The development of the Chinese navigation satellite system BeiDou has been extended to a global navigation satellite system (GNSS). In December 2011, the Chinese government released a specification document—a test version of a civil BeiDou-II signal called B1(I). A strong possibility exists that BeiDou-II (Chinese GNSS) will be adopted by North Korea in the near future. Therefore, research on BeiDou-II is essential. Since BeiDou-II is a newly-built system, few jamming effect analyses of its positioning signals have been performed. Thus, in this study, we analyze quality factors (Q) and the tolerable jamming signal power among two BeiDou-II civil signals, and two GPS civil signals, in three jamming conditions: band-limited white noise (BLWN), matched spectrum (MS), and continuous wave (CW). In addition, we present each jamming propagation range.DOI:http://dx.doi.org/10.11591/ijece.v2i6.181

Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information

Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information

Probabilistic Integrated Urban Inundation Modeling Using Sequential Data Assimilation

Urban inundation due to climate change and heavy rainfall is one of the most common natural disasters worldwide. However, it is still insufficient to obtain accurate urban inundation predictions due to various uncertainties coming from input forcing data, model parameters, and observations. Despite of numerous sophisticated data assimilation algorithms proposed to increase the certainty of predictions, there have been few attempts to combine data assimilation with integrated inundation models due to expensive computations and computational instability such as breach of conservation and momentum equations in the updating procedure. In this study, we propose a probabilistic integrated urban inundation modeling scheme using sequential data assimilation. The original integrated urban inundation model consists of a 2D inundation model on the ground surface and a 1D network model of sewer pipes, which are combined by a sub-model to exchange storm water between the ground surface and the sewerage system. In our method, uncertainties of modeling conditions are explicitly expressed by ensembles having different rainfall input, initial conditions, and model parameters. Then, particle filtering(PF), one of sequential data assimilation techniques for non-linear and non-Gaussian models, is applied to sequentially update model states and parameters when new observations are arrived from monitoring systems. Several synthetic experiments are implemented to demonstrate applicability of the proposed method in an urbanized area located in Osaka, Japan. The discussion will be focused on noise specification and updating methods in PF and comparison of accuracy between deterministic and probabilistic inundation modeling methods

Development of a multi-channel NIRS-USG hybrid imaging system for detecting prostate cancer and improving the accuracy of imaging-based diagnosis: a phantom study

Purpose This study aimed to develop a multi-channel near-infrared spectroscopy (NIRS) and ultrasonography (USG) fusion imaging system for imaging prostate cancer and to verify its diagnostic capability by applying the hybrid imaging system to a prostate cancer phantom. Methods A multi-channel NIRS system using the near-infrared 785-nm wavelength with 12 channels and four detectors was developed. After arranging the optical fibers around a USG transducer, we performed NIRS imaging and grayscale USG imaging simultaneously. Fusion imaging was obtained by processing incoming signals and the spatial reconstruction of NIRS, which corresponded with grayscale USG acquired at the same time. The NIRS-USG hybrid system was applied to a silicone-based optical phantom of the prostate gland containing prostate cancer to verify its diagnostic capability qualitatively. Results The NIRS-USG hybrid imaging system for prostate cancer imaging simultaneously provided anatomical and optical information with 2-dimensional registration. The hybrid imaging system showed more NIR attenuation over the prostate cancer model than over the model of normal prostate tissue. Its diagnostic capability to discriminate a focal area mimicking the optical properties of prostate cancer from the surrounding background mimicking the optical properties of normal prostate tissue was verified by applying the hybrid system to a silicone-based optical phantom of prostate cancer. Conclusion This study successfully demonstrated that the NIRS-USG hybrid system may serve as a new imaging method for improving the diagnostic accuracy of prostate cancer, with potential utility for future clinical applications