IDSDL: a sensitive intrusion detection system based on deep learning

Device-free passive (DfP) intrusion detection system is a system that can detect moving entities without attaching any device to the entities. To achieve good performance, the existing algorithms require proper access point (AP) deployment. It limits the applying scenario of those algorithms. We propose an intrusion detection system based on deep learning (IDSDL) with finer-grained channel state information (CSI) to free the AP position. A CSI phase propagation components decomposition algorithm is applied to obtain blurred components of CSI phase on several paths as a more sensitive detection signal. Convolutional neuron network (CNN) of deep learning is used to enable the computer to learn and detect intrusion without extracting numerical features. We prototype IDSDL to verify its performance and the experimental results indicate that IDSDL is effective and reliable.

Diurnal Cycles of Precipitation and Lightning in the Tropics Observed by TRMM3G68, GSMaP, LIS, and WWLLN

Diurnal cycles of precipitation and lightning are investigated by analyzing rain rates of the TRMM3G68 dataset, consisting of Precipitation Radar and Microwave Imager data only; rain rates of Global Satellite Mapping of Precipitation (GSMaP), for which infrared (IR) data are also used; lightning flash rates observed by TRMM Lightning Imaging Sensor (LIS); and lightning stroke rates of World Wide Lightning Location Network (WWLLN) over the tropics. Diurnal amplitudes relative to averages are generally larger for lightning than for precipitation. Over ocean, relative amplitudes are stronger in the stratocumulus deck region in the southeast Pacific than those over typical ocean regions. The phase of GSMaP is substantially delayed to TRMM3G68 due to the phase-delay problem of IR-based estimation. The diurnal peaks tend to occur between 1400 and 1800 LST over the continent after spatial averaging with a phase leading order of TRMM3G68, LIS, and WWLLN, and between 0000 and 0700 LST over oceanic regions where diurnal cycles are prominent in all datasets. Off-equatorward phase propagations are found in the precipitation in the Pacific and Indian Oceans. Over selected coastal regions, all data exhibit consistent oceanward phase propagation with the longest, medium, and shortest phase propagation distances for TRMM3G68 precipitation, WWLLN lightning, and LIS lightning, respectively, with a phase leading order of LIS, WWLLN, and TRMM3G68. The summertime diurnal cycle over the Gulf Stream also exhibits oceanward phase propagation, but with strong amplitude enhancement over the Gulf Stream. Diurnal cycle amplitude is also enhanced over the Kuroshio in the East China Sea in the baiu–mei-yu rainy season.

Compact Band-Selective Power Divider Using One-Dimensional Metamaterial Structure

A band-selective power divider is demonstrated for the first time. By replacing lumped element right-handed (RH) and left-handed (LH) transmission lines (TL) in a conventional Wilkinson power divider, it is possible to achieve both power division and filtering simultaneously. By utilizing the positive phase propagation property of an RHTL, which works as a low-pass filter, and the negative phase propagation property of an LHTL, which works as a high-pass filter, the band-selective quarter-wave sections required to construct a Wilkinson power divider are implemented. The fabricated circuit shows an insertion loss in the range 1.7 dB–2.5 dB in the passband, with the circuit dimensions of merely 12 mm by 10 mm.

Commonly used methods fail to detect known propagation speeds of simulated signals from time–longitude (Hovmöller) diagrams

This work examines the accuracy and validity of two variants of Radon transform and two variants of the two-dimensional fast Fourier transform (2-D FFT) that have been previously used for estimating the propagation speed of oceanic signals such as sea surface height anomalies (SSHAs) derived from satellite-borne altimeters based on time–longitude (Hovmöller) diagrams. The examination employs numerically simulated signals made up of 20 or 50 modes where one, randomly selected, mode has a larger amplitude than the uniform amplitude of the other modes. Since the dominant input mode is known ab initio, we can clearly define “success” in detecting its phase/propagation speed. We show that all previously employed variants fail to detect the phase speed of the dominant input mode when its amplitude is smaller than 5 times the amplitude of the other modes and that they successfully detect the phase speed of the dominant input mode only when its amplitude is at least 10 times the amplitude of the other modes. This requirement is an unrealistic limitation on oceanic observations such as SSHA. In addition, three of the variant methods detect a dominant mode even when all modes have the exact same amplitude. The accuracy with which the four methods identify a dominant input mode decreases with the increase in the number of modes in the signal. Our findings are relevant to the reliability of phase speed estimates of SSHA observations and the reported “too fast” a phase speed of baroclinic Rossby waves in the ocean.