This paper presents a bistatic remote sensing system to efficiently estimate the characteristics of sea swell near a harbor by receiving and processing global navigation satellite system signals transmitted in line-of-sight channels and fading multipath channels. The new system is designed to measure and monitor sea swell to improve the safety of mooring and navigation services in or around harbors, and long-term measurement also will provide valuable hydrologic data for harbor construction or reconstruction. The system uses two sets of antennas. One is a conventional antenna to receive line-of-sight signal and mitigate the disturbances from multiple propagation paths, and the other is a left hand circular polarization arrayed antenna to receive reflected signals from sea-surface. In particular, a wide bandwidth RF/IF front-end is designed to process reflected signals with high sampling frequency. A software receiver is developed to provide information from satellites and line-of-sight signals, and a wave characteristic estimator is also developed to process reflected signals. More specifically, correlators and Teager-Kaiser energy operator are combined to detect and depict reflected signals. Wave propagation of sea swell can be accurately mapped using intensity and relative time delays of reflected signals. The operational performance of the remote sensing system was also evaluated by numerical simulations. The results confirm that wavelength and wave period can be measured precisely by the proposed bistatic ocean wave remote sensing system.

This paper presents an experimental evaluation of an ocean wave remote sensing system that uses bistatic GPS signal reflection to estimate wave characteristics. In our previous paper, a bistatic ocean wave remote sensing system by GPS was proposed to estimate the characteristics of sea swell near a harbor, and was also evaluated by numerical simulations. In the next phase, a prototype system has been developed and some basic experiments have been carried out in a coastal area in order to evaluate the system experimentally. In this paper, we will outline the prototype system. The system mainly consists of an array antenna, a front-end, and an estimator for ocean wave characteristics. Next, we explain that the estimator for ocean wave characteristics can identify each signal reflected from the ocean waves. Finally, the experiments show that the prototype system can receive the reflected signals from the sea-surface near the coast, and estimate the wave period and wavelength in the direction of the array antenna.

Bitcoin is currently a hot issue worldwide, and it is expected to become a new legal tender that replaces the current currency started with El Salvador. Due to the nature of cryptocurrency, however, difficulties in tracking led to the arising of misuses and abuses. Consequently, the pain of innocent victims by exploiting these bitcoins abuse is also increasing. We propose a way to detect new signatures by applying two-fold NLP-based clustering techniques to text data of Bitcoin abuse reports received from actual victims. By clustering the reports of text data, we were able to cluster the message templates as the same campaigns. The new approach using the abuse massage template representing clustering as a signature for identifying abusers is much efficacious.