In this paper, a compact quasi‐elliptic stepped impedance resonator‐substrate integrated waveguide (SIR‐SIW) bandpass filter with multiple transmission zeros (TZs) has been proposed. The SIR‐SIW filter consists of SIW cavity and SIR. The employment of SIR makes it possible to realize multiple energy coupling paths within a compact area for introduction of multiple TZs. The SIW is used for its high Q, low loss characteristics. Besides, two TZs are introduced by the SIW. Including energy coupling path between source and load, totally four TZs besides the passband are realized. A miniature (0.3 λg2) four‐pole, four‐transmission zero filter with high selectivity is realized. Experimental verification is provided and a good agreement has been found between simulation and measurement.

A multi-longitudinal mode fiber laser sensor (MLMFLS) system based on a digital modulation/demodulation technique is proposed. To the best of the authors’ knowledge, this is the first digital vibration-demodulation system ever reported by a MLMFLS system. Multiple beat frequency signals (BFS) generated by the MLMFLS work as signal carriers of applied vibration signals. The vibration signals modulated on several BFS at different frequencies are simultaneously demodulated based on a multi-channel digital down-conversion technique by utilizing the digital universal software radio peripheral (USRP). The demodulated vibration signals from different signal channels are superposed by the USRP. Signal-to-noise ratio (SNR) of output vibration signal is highly improved, which increases sensing stability and accuracy of the system. This is really important for sensing of vibration signals that have an extremely low frequency or weak energy. Measurement results demonstrate that the sensing system has an excellent low frequency vibration-sensing capability, simple structure, high SNR, stability and accuracy.

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.SignificanceA multiplexed fiber laser sensing system for cell temperature is proposed. To the best of the authors’ knowledge, this is the first multilongitudinal mode (MLM) optical fiber laser sensor array designed for cell temperature sensing.AimA two-channel cell temperature sensing system with high sensitivity and real-time sensing capability is achieved. The temperature change of human hepatoellular carcinomas (HepG2) cells under the influence of exogenous chemical aflatoxin B1 (AFB1) can be monitored in real time.ApproachA fiber laser cavity consists of a pair of fiber Bragg gratings (FBGs) with matched central wavelengths and a piece of erbium-doped fiber (EDF). The static FBG is utilized for design of fiber laser cavity and laser modes selection. In comparison, the sensing FBG is used for cell temperature sensing. The sensing FBG has a length of 10 mm and a diameter of 200  μm. Beat frequency signals (BFS) are generated by MLM lasers after optical-to-electrical conversion at a photodetector. Frequency change of a BFS is closely related to the reflected wavelength change of the sensing FBG. Through frequency division multiplexing, two fiber laser cavities are designed in the sensing system for two-channel temperature sensing. Frequency shift of a BFS that represents temperature change of cells can be automatically recorded in seconds.ResultsA two-channel cell temperature sensing system is designed with high sensitivities of 101.62 and 119.82  kHz  /    °  C, respectively. The temperature change of HepG2 cells under the influence of exogenous chemical AFB1 is monitored in real time.ConclusionsThe proposed system has the advantages of simple structure, high sensitivity, and two-channel sensing capability. Our study provides a simple and effective method to design a fiber laser sensor system without complex demodulation techniques and expensive optical components.

Real-time people counting based on videos is one of the most popular projects in the construction of smart cities. To develop an accurate people counting approach, deep learning can be used as it greatly improves the accuracy of machine learning based approaches. To this end, we have previously proposed an accurate YOLO (You Only Look Once) based People Counting approach, dubbed YOLO-PC. However, the model of YOLO-PC was very large with an excessive number of parameters, thus it requires large storage space on the device and makes transmission on Internet a time consuming task. In this paper, a new real-time people counting method named as Squeeze YOLObased People Counting (S-YOLO-PC) is proposed. S-YOLO-PC uses the re layer of SqueezeeNet to optimize the network structure, which reduces the number of parameters used in the model without decreasing its accuracy. Based on the obtained the experimental results, S-YOLO-PC reduces the number of model parameters by 11.5% and 9% compared to YOLO and YOLO-PC, respectively. S-YOLO-PC can also detect and count people with 41 frames per second (FPS) with the average precision (AP) of person of 72%.