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A method for recognition of casting defects based on improved You Only Look Once (YOLO v3) is proposed to address the problems of slow detection speed, low detection efficiency, and poor robustness suffered from the current inspecting manually methods, which can improve the ability to detect defects, especially for tiny defects. Firstly, for obtained the industrial digital radiography images (DR images), we introduce the guide filtering technique to enhance the defects in these DR images, thus obtaining standard defect samples; Further, the defect samples are annotated to generate the defect detection data set for network training. In this article, the improved YOLOv3 network model structure is used to detect defects. Comparative experiments illustrate the proposed defect detection model for castings achieves better performance. Concretely, the experimental results show that the improved network model (YOLOv3_134) converges faster than the YOLOv3 network model and has better convergence than the YOLOv3 model. And the mean average precision (mAP) of the YOLOv3_134 is 26.1% higher than that of the original YOLOv3, which makes the YOLOv3_134 model-based casting defect detection method meet the industrial production requirements in terms of accuracy and speed.

Ferrites are promising nonmetallic materials used for the fabrication of low-noise magnetic shields because they possess high permeability and high electrical resistivity. However, large-sized ferrite components are difficult to fabricate or machine. In this study, we develop a cylindrical ferrite shield that consists of five annuli and two lids with an inner volume of φ11.2 cm × 22.5 cm. Although this structure contains gaps between different components, it eases considerably the fabrication and machining process as compared to the entire module. The magnetic noise is measured by a spin-exchange relaxation-free atomic magnetometer, and the detrimental effects of the gaps are analyzed quantificationally using the finite element method. Our research results indicate that compared with the ferrite shield without gaps, the magnetization noise increases by 34.1%. Nonetheless, the magnetic noise at the center of the ferrite shield achieves 5.5f -1/2 fT, which is much lower than that of μ-metal shields with a similar size. If the gap width can be reduced to be smaller than 0.01 mm, the increase of the magnetization noise will be less than 4.9%, which can be negligible in practical applications. Our study provides a low-cost, readily available, and low-noise ferrite shield structure.

With the increasing penetration of renewable distributed generations (DGs), large numbers of “energy prosumers” are emerging rapidly. There will be severe impacts on the utility grid if these renewable DGs are not managed properly. Smart electrical power devices which enable high flexibility in energy management, alleviation in harmonic pollutions and friendly interactions with the utility grid are needed urgently. To meet all these requirements, a novel energy router which enables a unique parallel operation mode to the energy prosumer is presented. Facilitated with a bi-directional DC/AC converter, a switch array module and a fuzzy logic based hierarchical control strategy, the presented energy router enables plug-and-play connections and reliable energy management for the energy prosumer. The switch array and the parallel mode enable the loads to be flexibly scheduled to reduce energy cost and improve system performance. MATLAB/Simulink model of the energy prosumer is set up and a fuzzy logic based hierarchical control strategy is implemented for transient power balance control in various operation modes. Simulation results have demonstrated high flexibility, stability and feasibility of the proposed energy router in energy management of the prosumer, which will contribute to the better utilization of the ever-growing renewable energies.

Recently, the face detection and alignment is so popular and widely used in many research and application fields. Many superior face detection algorithms such as multi-task cascade convolutional network have been presented. However, it has difficulty in predicting faces among the big scale images in real time due to its three stages cascade architecture with less optimization. In this paper, we propose a full GPU-based batch multi-task cascade convolutional network which is carefully designed and optimized in each step to gain a superior speed performance. In addition, we present a novel parallel memory allocation strategy, which further enables our algorithm to support the batch operation, so that the system throughput increases significantly. In the experiment, our method achieves up to 300fps, over 600% speedup with an equal accuracy over the state-of-the-art methods on the face detection benchmarks.

Due to their inherent topology characteristic, current source grid-connected photovoltaic inverters cannot realize low voltage ride through (LVRT) during a serious sag in the grid voltage. Based on mathematical models of three-phase current source grid-connected photovoltaic (PV) inverters, this paper analyzes quantitatively the relationship between steady-state DC-link current and grid voltage, and also derives the steady-state working range of the DC-link current in CSIs. Based on the steady-state working range of the DC-link current and the native characteristics of PV cells, this paper indicates the fundamental reason that three-phase current source inverter cannot realize LVRT. To solve this problem, an improved topology of a current source grid-connected photovoltaic inverter is adopted in this paper, where a chopper circuit is added in the DC link. Meanwhile, a novel control strategy is further proposed to realize LVRT under balanced and unbalanced grid voltage conditions. Finally, the simulation and experiment results verify the effectiveness of the proposed method.

In this paper, a novel WR-2.8 band (260-400 GHz) pseudo-elliptic waveguide bandpass filter (BPF) based on a singlet and an extracted pole resonator is proposed. The singlet based on TE301 mode and extracted pole resonant cavities is developed to generate two transmission zeros (TZs) on both sides of the passband in order to achieve high selectivity. The mechanism of TZs generation of both structures is analyzed in this paper, and TZs position is predicted precisely. Furthermore, each TZ position can be controlled independently by changing the dimensions of resonant cavities. The proposed filter fabricated by conventional computer numerical control (CNC) milling technology exhibits an insertion loss (IL) around 0.7dB, a 3-dB fractional bandwidth (FBW) of 9.9% centered at 357GHz and an ultra-high selectivity with a 0.87 30-dB rectangular factor which is all in good agreement with the simulations. To the best of the author's knowledge, 0.87 is the highest 30-dB rectangular factor among such wide fractional bandwidth THz BPF in the open literature. This high-performance filter is capable of improving the sideband rejection receiver performance.

In this study, we demonstrate a non-modulated triaxial magnetic field compensation method for spin-exchange relaxation-free (SERF) atomic magnetometers. We realize simultaneous compensation of the magnetic field along the pump and probe directions by maximizing the first order differential value of the zero-field resonance signal. The magnetic field perpendicular to the pump-probe plane is compensated by zeroing the DC response of the magnetometer. The zero-field resonance is obtained by applying a linearly changed magnetic field along the direction perpendicular to that of the pump-probe plane. The first order differential of the zero-field resonance is acquired using the second order central difference method in real time. Compared with the conventional compensation methods, this method does not involve modulation and demodulation. Therefore, it requires no lock-in amplifier, thus making it more applicable in miniature atomic devices. Moreover, this method compensates the magnetic field along the pump and probe directions using only one criterion. It avoids the cross-talk effect between the pump and probe directions in the presence of non-orthogonal coils. The experiment results show that the compensation resolution is 9 pT, 7 pT and 0.05 pT for the probe, pump, and direction perpendicular to the pump-probe plane, respectively.

Infrared small target detection under complex background is of great significance in the field of remote sensing, such as optical remote sensing, infrared precise guidance, infrared surveillance, and night navigation. Because of low-contrast and complex-background clutters of infrared images, infrared small target detection under complex background is difficult and has a serious false alarm. In this paper, a difference-based local contrast method is proposed to improve the detection performance. First, a median filtering process is used to reduce pixel-sized noises, and infrared image after filtering is divided into a series of sub-images. Then, a difference-based local contrast measure based on contrast mechanism is calculated for generating the saliency map, which can exceedingly improve the detection rate and reduce the false alarm rate. Eventually, an adaptive threshold is used to extract the target sub-image. Experiments on five real infrared small target image datasets show that the proposed method is robust and effective with great respect to detection accuracy. Our method can achieve a higher detection rate and lower false alarm rate under complex background with better performance in target enhancement and background suppression compared with the traditional algorithms.

The ferrite magnetic shield can provide a low-noise magnetic environment for various ultrahigh-sensitivity measurements. The low-frequency complex permeability, which determines the magnetic hysteresis noise and the shielding factor, is a key parameter of the ferrite shield and thus should be measured accurately. In this paper, the measurement error of conventional coil method is analyzed at low frequency, and an improved method is proposed which could eliminate the measurement error introduced by the wire resistance. Using this method, four ferrite samples made of PC40 and PC47 materials are measured. The measurement accuracy of the low-frequency complex permeability has improved by two orders of magnitude. On the basis of the measurement results, magnetic hysteresis noise and the shielding factor of ferrite shields are calculated. The calculated results of the noise analysis indicate that the PC40 material has lower magnetic hysteresis noise. This study can help select the ferrite materials and estimate the performance for low-noise magnetic shield design.

Wireless sensor network (WSN) is an emerging technology with a wide range of potential applications in smart buildings. The measuring process by using WSNs in the actual environment always introduces noise, errors, accidents, and other potential outliers to the data collected by the sensors. It is crucial to establish an effective approach for outlier detection and recovery in the real applications of WSNs. In this paper, we propose an outlier detection and recovery approach using artificial neural network (ANN), which can be used to determine whether the temperature values measured by the sensors in WSNs are outliers. The experimental results in real building show that the proposed ANN-based models can provide a reasonably good prediction of the temperature and high accuracy in buildings compared with the hidden Markov model (HMM)-based approach, which can potentially be used for outlier detecting and thermal controlling in the Internet of Things (IoT) applications.

Nowadays, more and more new cryptographic protocols are emerging, and the security analysis of emerging cryptographic protocols is increasingly important. The logic of events is an axiomatic method based on theorem proving, designed around message automation with actions for possible protocol steps; it figured out types of information transmitted in the protocols and also presented novel proof rules and mechanism. However, with the emergence of various cryptographic protocols, the logic of events lacks corresponding axioms and rules in the process of proving certain cryptographic protocols, so it needs a further extension. Based on the logical framework of protocol composition logic, this paper presents a refined theory of the logic of events called LoET-E, in which the novel rules about the freshness of nonces, the event attributes of messages, and the states of the predicate is presented; the concepts of $Fresh$ , $Gen$ and $FirstSend$ is introduced; and the definition of $has$ and the honesty axiom of LoET is extended. The refined theory can guarantee the correctness, integrity, and validity of the original axioms, ensure the consistency of event classes and basic sequences in the proof process, reduce the complexity and redundancy in the protocol analysis process, and most importantly, extend the provable range of cryptographic protocols.

The near field communication (NFC) is widely used on mobile devices and make it possible to take advantage of NFC system to complete mobile payment. But with the development of NFC, its problem are increasingly exposed, especially the security and privacy of authentication. The logic of events is a formal method to describe the protocol state transition and algorithm in concurrent and distributed systems, which can be used to prove the security of network protocols. Based on logic of events, we propose migration rule and derive inheritability to reduce redundancy and complexity of protocol analysis procedure and improve efficiency of protocol analysis. We study the KerNeeS protocol which providing mutual authentication between POS and NFC phone, and conclude that the protocol can guarantee mutual authentication property between entities involved in the payment for secure payment transactions. The logic of events can be applied to the formal analysis of similar mobile payment protocols.

Nano-devices have great potential to play a vital role in future medical diagnostics and treatment technologies because of its non-invasive nature and ability to reach delicate body sites easily as compared with conventional devices. In this paper, a novel concept of cooperative communication for in vivo nano-network is presented to enhance the communication among these devices. The effect on the system outage probability performance is conducted for various parameters, including relay placement, number of relays, transmit power, bandwidth, and carrier frequency. Results show approximately a tenfold increase in the system outage performance whenever an additional relay is included in the cooperative network, and hence show a great potential of using cooperative communication to enhance the performance of nano-network at terahertz frequencies.

The envisioned dense nano-network inside the human body at terahertz (THz) frequency suffers a communication performance degradation among nano-devices. The reason for this performance limitation is not only the path loss and molecular absorption noise, but also the presence of multi-user interference and the interference caused by utilising any communication scheme, such as time spread ON-OFF keying (TS-OOK). In this paper, an interference model utilising TS-OOK as a communication scheme of the THz communication channel inside the human body has been developed and the probability distribution of signal-to-interference-plus-noise ratio (SINR) for THz communication within different human tissues, such as blood, skin, and fat, has been analyzed and presented. In addition, this paper evaluates the performance degradation by investigating the mean values of SINR under different node densities in the area and the probabilities of transmitting pulses. It results in the conclusion that the interference restrains the achievable communication distance to approximate 1 mm, and more specific range depends on the particular transmission circumstance. Results presented in this paper also show that by controlling the pulse transmission probability and node density, the system performance can be ameliorated. In particular, SINR of in vivo THz communication between the deterministic targeted transmitter and the receiver with random interfering nodes in the medium improves about 10 dB, when the node density decreases one order. The SINR increases approximate 5 and 2 dB, when the pulse transmitting probability drops from 0.5 to 0.1 and 0.9 to 0.5.

This paper focuses on the analysis of cultivated collagen samples at the terahertz (THz) band using double debye model parameter extraction. Based on measured electrical and optical parameters, we propose a model to describe such parameters extracted with a global optimisation method, namely, particle swarm optimisation. Comparing the measured data with ones in the open literature, it is evident that using only cultivated collagen is not sufficient to represent the performance of the epidermis layer of the skin tissue at the THz band of interest. The results show that the differences between the measured data and published ones are as high as 14 and 6 for the real and imaginary values of the dielectric constant, respectively. Our proposed double debye model agrees well with the measured data.

Nano-communication-based devices have the potential to play a vital role in future healthcare technologies by improving the quality of human life. Its application in medical diagnostics and treatment has a great potential, because of its ability to access small and delicate body sites noninvasively, where conventional medical devices fall short. In this paper, the state of the art in this field is presented to provide a comprehensive understanding of current models, considering various communication paradigms, antenna design issues, radio channel models based on numerical and experimental analysis and network, and system models for such networks. Finally, open research areas are identified for the future directions within the field.