Due to the existence of channel difference, allocating network resources reasonably in multi-channel scenarios is much more complicated than that in single-channel cases. This paper designs a distributed channel-assignment and scheduling algorithm for multi-channel multi-interface wireless networks, i.e., a resource allocation scheme in MAC layer. Via employing the random access technique and a tuple-based model, the proposed mechanism is proved to be able to guarantee a reliable throughput capacity region with complexity independent of the network size. On the other hand, the diversity of interfaces is further considered in addition to channel difference, which improves the adaptability of the developed algorithm.

We propose rolling-shutter (RS)-based asynchronous optical camera communication (OCC) with a variable symbol rate based on a cycle pattern of the receiver’s symbols which is uniquely determined by the ratio of the line interval of RS to the transmitter’s symbol length. RS-based asynchronous OCC has been experimentally demonstrated using various Android smartphones’ built-in cameras with a variable symbol rate when the ratio of the line interval of RS to the symbol length is expressed as a simple integer ratio. Error-free transmission has been achieved from 4 to 14 kilo-symbols per second (symbols/s) using smartphones’ 30-frame-per-second (fps) image sensors.

We propose a new CAPTCHA scheme that uses random dot patterns (RDPs) to prevent highly-developed bots attacks. Human beings can recognize a moving figure filled by a RDP from a background that is filled by another RDP; however, it is impossible to find such figures when they are stationary. Since image recognition by bots is usually carried out frame by frame, it is hard for bots to recognize such moving figures. The proposed CAPTCHA scheme exploits this characteristic. Several experiments were carried out to confirm that the proposed CAPTCHA scheme is usable enough and has enough resistance against bot attacks.

Currently, personal authentication is used in many areas, and typically involves password authentication with a keyboard, but authentication information is easily leaked by shoulder surfing. We previously proposed an authentication method using mouse operation, which can be used with shared PCs and in public places. However, its usability was low. Thus, here we propose an improved method that can be performed by operating a mouse to manipulate cells of a number matrix displayed on a screen. We implemented the proposed method and conducted experiments on its usability and shoulder-surfing resistance. Questionnaire results showed that the usability of the proposed method is improved, and no shoulder surfer could obtain complete authentication information.

This paper proposes an evaluation method for common mode (CM) and differential mode (DM) of conducted emission in the power line measured with a Vector signal analyzer (VSA). The termination disturbance voltage of the two LISN (line impedance stabilization network) are synchronously measured with a 2ch VSA. The results of vector signal processing in the proposed method in experimentally validation by comparing with the results of conventional method for noise mode separation by using CMDM switch.

Polarimetric similarity is a parameter for measuring the similarity between two scattering mechanisms. In this paper, we propose a novel model-based target classification technique using a compensated polarimetric similarity parameter between two coherency matrices. In general, the ensemble average coherency matrix elements have magnitude imbalance, thus the contribution degree to the polarimetric similarity differs for each element. We illustrate how to compensate the contribution degree, and then the proposed method is tested on L-band fully polarimetric ALOS-2/PALSAR-2 data sets by using 4 theoretical scattering models (surface scattering, double-bounce scattering, volume scattering, and 22.5° oriented dihedral scattering). The classification results show that the new compensation scheme serves to better classification.