A honeycomb structure with a negative Poisson's ratio (NPR) was designed, fabricated, and analyzed for utilization in personal protective clothing (PPC). The mechanical properties were investigated using a quasi-static mechanical testing and the Hopkinson pressure bar experimental system, and results were compared with similar samples containing regular hexagonal and regular quadrilateral honeycomb structures. The experimental results showed that under quasi-static loadings, the concave honeycomb structure had the highest compressive modulus and yield strength, which produced the highest strain absorption energy, anti-deformation performance and energy absorption. When exposed to a dynamic load at a high strain rate, the concave honeycomb also exhibited the highest dynamic compression modulus, the best impact resistance and best energy absorption among the three structures. In summary, the concave honeycomb structure was more resistant to deformation and had higher impact resistance than the regular hexagonal and regular quadrilateral honeycombs, and exhibited better energy absorption, which makes it a good candidate for application as a personal safety protection material.

Unmanned weapons have great potential to be widely used in future wars. The gaze-based aiming technology can be applied to control pan-tilt weapon systems remotely with high precision and efficiency. Gaze direction is related to head motion, which is a combination of head and eye movements. In this paper, a head motion detection method is proposed, which is based on the fusion of inertial and vision information. The inertial sensors can measure rotation in high-frequency with good performance, while vision sensors are able to eliminate drifts. By combining the characteristics of both sensors, the proposed approach achieves the effect of high-frequency, real-time, and drift-free head motion detection. The experiments show that our method can smooth the outputs, constrain drifts of inertial measurements, and achieve high detection accuracy.

Pilot contamination can bring up a grave impairment in the performance of massive multiple-input multiple-output(MIMO) systems. In this paper, an improved time-shifted pilot scheme is proposed to reduce the pilot contamination, where orthogonal pilots are employed in the same group to eliminate the residual intra-group interference existing in the original time-shifted pilot scheme. Meanwhile, the rigorous closed-form expressions of both downlink and uplink transmission rates with a finite number of antennas are derived, and it is shown that the intra-group interference can be completely eliminated by the proposed scheme. Simulation results demonstrate that both downlink and uplink transmission rates are significantly improved by employing the proposed scheme.

To deal with the problem that the initial velocity of the bullet is difficult to increase, the research on the super-high initial velocity propulsion in the barrel weapon with an adaptive pressure-maintaining chamber are conducted. Considering the law of gun-powder burning and the flow characteristics of gun-powder gas in multi-chamber, the scheme of super-high initial velocity propulsion with an adaptive pressure-maintaining chamber is designed, the ballistic model of the barrel weapon with super-high velocity bullet propulsion is established. The research results show that the technical scheme can greatly increase the initial velocity of the bullet with the peak pressure keeping nearly the same as the tradition barrel weapon. The research results can provide a theoretical foundation to significantly increase the initial velocity in barrel weapons using solid propellants, and have an important reference value to comprehensively increase the power of the barrel weapons.

The automatic detection of cardiac arrhythmias through remote monitoring is still a challenging task since electrocardiograms (ECGs) are easily contaminated by physiological artifacts and external noises, and these morphological characteristics show significant variations for different patients. A fast patient-specific arrhythmia diagnosis classifier scheme is proposed, in which a wavelet adaptive threshold denoising is combined with quantum genetic algorithm (QAG) based on least squares twin support vector machine (LSTSVM). The wavelet adaptive threshold denoising is employed for noise reduction, and then morphological features combined with the timing interval features are extracted to evaluate the classifier. For each patient, an individual and fast classifier will be trained by common and patient-specific training data. Following the recommendations of the Association for the Advancements of Medical Instrumentation (AAMI), experimental results over the MIT-BIH arrhythmia benchmark database demonstrated that our proposed method achieved the average detection accuracy of 98.22%,99.65% and 99.41% for the abnormal, ventricular ectopic beats(VEBs) and supra-VEBs(SVEBs), respectively. Besides the detection accuracy, sensitivity and specificity, our proposed method consumes the less CPU running time compared with the other representative state of the art methods. It can be ported to Android based embedded system, henceforth suitable for a wearable device.

An assessment of the new energy consumption capacity of the grid can help to improve new energy efficiency and its planning and development. The annual capacity of multi-regional new energy consumption is affected by the new energy installed capacity of each region, the output of thermal power units, the load size, and the exchange capacity between regional tie lines. In this paper, a real-time data processing method of a province is proposed, and a raw data processing method with dimensionality reduction equivalent is proposed. From the perspective of new installed capacity of new energy across regions, we obtain the assessment of the capacity of wind power photovoltaic bases in a given scenario, and propose new installed capacity for wind, light and energy storage power stations.

Acute myocardial infarction (AMI) is a major health problem leading to high rates of mortality and morbidity. Biomarker cardiac troponin I (cTnI) has shown high sensitivity and specificity towards AMI detection, and has been regarded as "gold standard". An ultrasensitive method to detect cTnI with low concentration in human fluid is essential. In this paper, we developed an aptamer-based assay coupled with rolling circle amplification (RCA) and molecular beacon probe for sensitive detection of cTnI. In this strategy, aptamer acts as a bridge to communicate between oligonucleotides and cTnI. RCA reaction produces a single-stranded tandem repeated copy of the circular template, which are recognized by fluorescence molecular beacon probe. With this strategy, highly sensitive and specific detection of cTnI was realized with the lowest detectable concentration of 7.24 pg/mL. The developed aptamer-RCA assay can be a promising tool in clinical samples analysis. The assay can also analyze other disease-related biomarkers by replacing the aptamer.

A novel method of scheme design is proposed for power shifting transmissions of parallel hybrid electric vehicles (HEVs). First, shift sequences considering the path of power flow and shift logics are analyzed based on the graph theory model, abstracted from the degree-of-freedom (DOF) of the schemes. Second, the scheme of gear-pair and shaft, defined as the scheme that ignores the arrangement of synchronizers, is derived from the basic configuration, defined as the scheme of gear-pair and shaft that contains only one of each type of the variable connections, and the numbers of each type of the variable connections. Finally, a multi-parameter scheme, including the arrangement of synchronizers and gear ratios, is designed to optimize the results of synthesis. This method helps to gain a deeper understanding of the systematic design of other fixed gear transmission schemes, such as automated mechanical transmission, dual clutch transmission, and even some novel multi-input transmission.

Unlike named entity recognition (NER) for English, the absence of word boundaries reduces the final accuracy for Chinese NER. To avoid accumulated error introduced by word segmentation, a deep model extracting character-level features is carefully built and becomes a basis for a new Chinese NER method, which is proposed in this paper. This method converts the raw text to a character vector sequence, extracts global text features with a bidirectional long short-term memory and extracts local text features with a soft attention model. A linear chain conditional random field is also used to label all the characters with the help of the global and local text features. Experiments based on the Microsoft Research Asia (MSRA) dataset are designed and implemented. Results show that the proposed method has good performance compared to other methods, which proves that the global and local text features extracted have a positive influence on Chinese NER. For more variety in the test domains, a resume dataset from Sina Finance is also used to prove the effectiveness of the proposed method.

To segment high-resolution remote sensing images (RSIs) accurately on an object level and meet the precise boundary dividing requirement, an improved superpixel segmentation and region merging algorithm is proposed. Simple linear iterative clustering (SLIC) is widely used because of its advantages in performance and effect; however, it causes over-segmentation, which is very disadvantageous to information extraction. In this proposed method, SLIC is firstly adopted for initial superpixel partition. The second stage follows the iterative merging procedure, which uses a hierarchical clustering algorithm and introduces a local binary pattern (LBP) texture feature operator during the process of merging. The experimental results indicate that the proposed method achieved a good segmentation and region merging performance, and worked effectively on cloud detection preprocessing in high-resolution RSIs with cloud and snow overlap situations.

The null space of the 6-DOF gain decoupling matrix of actuators and a modified velocity feedback controller are adopted to suppress the vibration of the wafer stage during exposure. To deal with varying flexibilities at different performance locations, the vibration controller is designed to be a time-variant linear quadratic regulator, using the conventional gain scheduling method, which could provide good vibration control for each field under exposure. This control method can guarantee the stability of the closed-loop system and will not deteriorate the rigid modes control of the wafer stage. To minimize the control spillover caused by the higher uncontrolled modes, actuator placement is optimized to minimize their controllability grammians in modal coordinates. An unconstrained rectangular plate is used to represent the fine stage of the wafer stage. Effectiveness of the proposed method is verified on the plate through a closed-loop simulation.

A manipulator-type docking hardware-in-the-loop (HIL) simulation system is proposed in this paper, with further development of the space docking technology and corresponding requirements of the engineering project. First, the structure of the manipulator-type HIL simulation system is explained. The mass and the flexibility of the manipulator has an important influence on the stability of the HIL system, which is the premise of accurately simulating actual space docking. Thus, the docking HIL simulation models of rigid, flexible and flexible-light space manipulators are established. The characteristics of the three HIL systems are studied from three important aspects: the system parameter configuration relation, the system stability condition and the dynamics frequency simulation ability. The key conclusions obtained were that the system satisfies stability or reproduction accuracy. Meanwhile, the influence of different manipulators on the system stability is further analyzed. The accuracy of the calculated results is verified experimentally.

A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed, which uses multiple single-constrained subspace projection parallel filters. If the direction of arrival (DOA) of a satellite signal is unknown, the traditional subspace projection anti-jamming algorithm cannot form the correct beam pointing. To overcome the problem of the traditional subspace projection algorithm, multiple single-constrained subspace projection parallel filters are used. Every single-constrained anti-jamming subspace projection algorithm obtains the optimal weight vector by searching the DOA of the satellite signal and uses the output of cross correlation as a decision criterion. Test results show that the algorithm can suppress the jamming effectively, and generate high gain toward the desired signal. The research provides a new idea for the engineering implementation of a multi-beam anti-jamming algorithm based on subspace projection.

A multi-residual module stacked hourglass network (MRSH) was proposed to improve the accuracy and robustness of human body pose estimation. The network uses multiple hourglass sub-networks and three new residual modules. In the hourglass sub-network, the large receptive field residual module (LRFRM) and the multi-scale residual module (MSRM) are first used to learn the spatial relationship between features and body parts at various scales. Only the improved residual module (IRM) is used when the resolution is minimized. The final network uses four stacked hourglass sub-networks, with intermediate supervision at the end of each hourglass, repeating high-low (from high resolution to low resolution) and low-high (from low resolution to high resolution) learning. The network was tested on the public datasets of Leeds sports poses (LSP) and MPII human pose. The experimental results show that the proposed network has better performance in human pose estimation.

Under the conditions of joint torque output dead-zone and external disturbance, the trajectory tracking and vibration suppression for a free-floating space robot (FFSR) system with elastic base and flexible links were discussed. First, using the Lagrange equation of the second kind, the dynamic model of the system was derived. Second, utilizing singular perturbation theory, a slow subsystem describing the rigid motion and a fast subsystem corresponding to flexible vibration were obtained. For the slow subsystem, when the width of dead-zone is uncertain, a dead-zone pre-compensator was designed to eliminate the impact of joint torque output dead-zone, and an integral sliding mode neural network control was proposed. The integral sliding mode term can reduce the steady state error. For the fast subsystem, an optimal linear quadratic regulator(LQR) controller was adopted to damp out the vibration of the flexible links and elastic base simultaneously. Finally, computer simulations show the effectiveness of the compound control method.

A practical method is proposed to search for periodic orbits of elongated asteroids. The method obtains required initial variables of periodic orbits by using the rotating mass dipole with appropriate parameters, and then implement local iterations to obtain the real orbits over an asteroid in the polyhedral model. In this paper the dipole and polyhedral models, and list detailed procedures of the searching method are introduced. A planar single lobe orbit is presented to evaluate the effectiveness of the method, with the asteroid 216 Kleopatra of the triple asteroid system as a representative elongated body. By applying the above method, ten families of periodic orbits around Kleopatra are identified and discussed with respect to their orbital stabilities and periods. One sample of the sombrero orbit is checked by calculating 1.000 hours to examine its orbital behavior. Besides the above orbits, the intriguing head-surrounding orbit is also analyzed.