In this paper, a novel multilayer substrate integrated waveguide (SIW) four-way out-of-phase power divider is proposed. It is realized by 3D mode coupling, on multilayer substrates. The structure consists of vertical Y-junction, lateral T-junction of SIW and lateral Y-junction of half-mode SIW. The advantages of the proposed structure are its low cost and ease of fabrication. Also, it can be integrated easily with other planar circuits such as microstrip circuits. An experimental circuit is designed and fabricated using the traditional printed circuit board technology. The simulated and measured results show that the return loss of the input port is above 15 dB over 8 to 11.8 GHz and transmissions are about -7.6±1.6 dB in the passband. It is expected that the proposed the proposed power divider will play an important role in the future integration of compact multilayer SIW circuits and systems.

Due to the rapid development of small satellite technology and the advantages of LEO satellite with low delay and low propagation loss as compared with the traditional GEO satellite, the broadband LEO constellation satellite communication system has gradually become one of the most important hot spots in the field of satellite communications. Many countries and satellite communication companies in the world are formulating the project of broadband satellite communication system. The broadband satellite communication system is different from the traditional satellite communication system. The former requires a higher transmission rate. In the case of high-speed transmission, if the low elevation constellation is adopted, the satellite beam will be too much, which will increase the complexity of the satellite. It is difficult to realize the low-cost satellite. By comparing the complexity of satellite realization under different elevation angles to meet the requirement of terminal speed through link computation, this paper puts forward the conception of building broadband LEO constellation satellite communication system with high elevation angle. The constraint relation between satellite orbit altitude and user edge communication elevation angle is proposed by theoretical Eq. deduction. And the simulation is carried out for the satellite orbit altitude and edge communication elevation angle.

In the context of compressed sensing (CS), simultaneous orthogonal matching pursuit (SOMP) algorithm is an important iterative greedy algorithm for multiple measurement matrix vectors sharing the same non-zero locations. Restricted isometry property (RIP) of measurement matrix is an effective tool for analyzing the convergence of CS algorithms. Based on the RIP of measurement matrix, this paper shows that for the K-row sparse recovery, the restricted isometry constant (RIC) is improved to $delta_{K+1}<rac{sqrt{4K+1}-1}{2K}$ for SOMP algorithm. In addition, based on this RIC, this paper obtains sufficient conditions that ensure the convergence of SOMP algorithm in noisy case.

This paper describes the research results of three dimensional parameter representation of human arm motion, image synthesis and intelligent transmission for sign language communication between Japan and China using a personal computer.

This paper studies the multi-link multi-antenna amplify-and-forward (AF) relay system, in which multiple source-destination pairs communicate with the aid of an energy harvesting (EH)-enabled relay and the relay utilizes the power splitting (PS) protocol to accomplish simultaneous EH and information forwarding (IF). Specifically, independent PS, i.e., allow each antenna to have an individual PS factor, and cooperative power allocation (PA) i.e., adaptively allocate the harvested energy to each channel, are proposed to increase the signal processing degrees of freedom and energy utilization. Our objective is to maximize the minimum rate of all source-destination pairs, i.e., the max-min rate, by jointly optimizing the PS and PA strategies. The optimization problem is first established for the ideal channel state information (CSI) model. To solve the formulated non-convex problem, the optimal forwarding matrix is derived and an auxiliary variable is introduced to remove the coupling of transmission rates in two slots, following which a bi-level iteration algorithm is proposed to determine the optimal PS and PA strategy by jointly utilizing the bisection and golden section methods. The proposal is then extended into the partial CSI model, and the final transmission rate for each source-destination pair is modified by treating the CSI error as random noise. With a similar analysis, it is proved that the proposed bi-level algorithm can also solve the joint PS and PA optimization problem in the partial CSI model. Simulation results show that the proposed algorithm works well in both ideal CSI and partial CSI models, and by means of independent PS and cooperative PA, the achieved max-min rate is greatly improved over existing non-EH-enabled and EH-enabled relay schemes, especially when the signal processing noise at the relay is large and the sources use quite different transmit powers.

The deep neural named entity recognition model automatically learns and extracts the features of entities and solves the problem of the traditional model relying heavily on complex feature engineering and obscure professional knowledge. This issue has become a hot topic in recent years. Existing deep neural models only involve simple character learning and extraction methods, which limit their capability. To further explore the performance of deep neural models, we propose two character feature learning models based on convolution neural network and long short-term memory network. These two models consider the local semantic and position features of word characters. Experiments conducted on the CoNLL-2003 dataset show that the proposed models outperform traditional ones and demonstrate excellent performance.

Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions use machine learning methods to learn the low-dimensional distributed representations of entities and relationships to complete the knowledge graph. Among them, translation models obtain excellent performance. However, the proposed translation models do not adequately consider the indirect relationships among entities, affecting the precision of the representation. Based on the long short-term memory neural network and existing translation models, we propose a multiple-module hybrid neural network model called TransP. By modeling the entity paths and their relationship paths, TransP can effectively excavate the indirect relationships among the entities, and thus, improve the quality of knowledge graph completion tasks. Experimental results show that TransP outperforms state-of-the-art models in the entity prediction task, and achieves the comparable performance with previous models in the relationship prediction task.

Existing fault localization based on neural networks utilize the information of whether a statement is executed or not executed to identify suspicious statements potentially responsible for a failure. However, the information just shows the binary execution states of a statement, and cannot show how important a statement is in executions. Consequently, it may degrade fault localization effectiveness. To address this issue, this paper proposes TFIDF-FL by using term frequency-inverse document frequency to identify a high or low degree of the influence of a statement in an execution. Our empirical results on 8 real-world programs show that TFIDF-FL significantly improves fault localization effectiveness.

This paper presents the electrical contact behaviors of Au-plated material at super low making and breaking velocity conditions by introducing our new designed test rig. The fundamental phenomena in the contact voltage and contact force versus piezoactuator displacement curves were investigated under the load current of 1A and velocity of 50,nm/s. From the repetitive experimental results, we found that the adhesion phenomena during the unloading process are closely correlative with the initial contact stage in the loading process. Furthermore, a mathematical model which is relative to the variation of contact force in loading is built, thus the physical mechanism of adhesion and principal factors of gold-plated materials are discussed. Finally, the physical process of molten bridge under the no mechanical contact situation is also analyzed in detail.

There has been increasing demand to research the measuring method to characterize the batch consistency of contact rivets. An automated test equipment has been described that makes it possible to measure the electrical contact resistance with high efficiency. The relationship between contact force and contact resistance during the loading and unloading process was measured explicitly using AgPd alloy, stainless steel and sapphire substrate material with Au coatings as sphere indenters separately. To explain the phenomena of contact resistance decreasing more slowly than the traditional theoretical results during loading, the indenter with coating and rivet are modeled by using the commercial FEM software COMSOL Multiphysics. Besides the constriction resistance, the transition region Au coating resistance and the bulk resistance of the substrate are deduced from the simulated current lines profiles and iso-potentials. The difference of electrical conductivity between indenter material and gold coating is the reason for the occurrence of the transition region.

In this paper, resource-efficient multiple description coding (MDC) multicast is investigated in cognitive radio networks with the consideration of imperfect spectrum sensing and imperfect channel feedback. Our objective is to maximize the system goodput, which is defined as the total successfully received data rate of all multicast users, while guaranteeing the maximum transmit power budget and the maximum average received interference constraint. Owing to the uncertainty of the spectrum state and the non-closed-form expression of the objective function, it is difficult to solve the problem directly. To circumvent this problem, a pretreatment is performed, in which we first estimate the real spectrum state of primary users and then propose a Gaussian approximation for the probability density functions of transmission channel gains to simplify the computation of the objective function. Thereafter, a two-stage resource allocation algorithm is presented to accomplish the subcarrier assignment, the optimal transmit channel gain to interference plus noise ratio (T-CINR) setting, and the transmit power allocation separately. Simulation results show that the proposed scheme is able to offset more than 80% of the performance loss caused by imperfect channel feedback when the feedback error is not high, while keeping the average interference on primary users below the prescribed threshold.

This paper studies the energy-saving problem in cognitive multicast orthogonal frequency-division multiplexing (OFDM) systems, for which a time-frequency two-dimensional model is established to enable the system energy conservation through joint temporal and spectral adaptations. The formulated two-dimensional problem, minimizing the total power consumption whilst guaranteeing the minimal-rate requirement for each multicast session and constraining the maximal perceived interference in each timeslot for the active primary user, is categorized as mixed integer non-convex programming, whose optimal solution is intractable in general. However, based on the time-sharing property, an asymptotically optimal algorithm is proposed by jointly iterating spectrum element (SE) assignment and power allocation. Moreover, a suboptimal algorithm, which carries out SE assignment and power allocation sequentially, is presented as well to reduce the computation complexity. Simulation results show the proposed joint algorithm can achieve the near-optimal solution, and the proposed sequential algorithm approximates to the joint one very well with a gap of less than 3%. Compared with the existing slot-by-slot energy-saving algorithms, the total power consumption is considerably decreased due to the combined exploitation of time and frequency dimensions.

Cognitive orthogonal frequency-division multiplexing (OFDM) systems are spectrum-efficient yet vulnerable to intercarrier interference (ICI), especially in high-mobility scenarios. In this paper, the energy efficiency optimization problem in high-mobility cognitive OFDM system is considered. The aim is to maximize the energy efficiency by adapting subcarrier bandwidth, power allocation and sensing duration in the presence of ICI, under the constraints of the total power budget of secondary networks, the probabilistic interference limits for the protection of primary networks, and the subcarrier spacing restriction for high-mobility OFDM systems. In order to tackle the intractable non-convex optimization problem induced by ICI, an ICI-aware power allocation algorithm is proposed, by referring to noncooperative game theory. Moreover, a near-optimal subcarrier bandwidth search algorithm based on golden section methods is also presented to maximize the system energy efficiency. Simulation results show that the proposed algorithms can achieve a considerable energy efficiency improvement by up to 133% compared to the traditional static subcarrier bandwidth and power allocation schemes.

We propose a new framework named ROICF based on reinforcement learning orienting reliable compilation optimization sequence generation. On the foundation of the LLVM standard compilation optimization passes, we can obtain specific effective phase ordering for different programs to improve program reliability.

Nowadays electronic devices and systems are widely used in various dynamic environments. However, they cause electrical contact instability that can easily be ignored. This phenomenon is considered as contact failure caused by a dynamic influence. In this paper, the investigation of contact failure caused by dynamic influences and analysis method for such contact failure are discussed. The results show that a dynamic influence could not be well covered in the experimental testing for a new product.

This paper focuses on the numerical and experimental investigations of the influence of two polymers (PA6 and POM) on the arc behavior during arc motion process. The mathematical model of 3-dimentional air arc plasma considering the ablation of lateral walls is built based on magnetic hydro-dynamics (MHD). By adopting the commercial computational fluid dynamics (CFD) package based on control-volume method, the above MHD model is solved and the distribution of temperature field, concentration field, flow field and electrical potential field in the arc chamber are calculated. The simulation results indicate that the vapor concentration behind the arc column is higher than that in front of the arc column because of the existence of "double vortices" in the arc chamber. The use of polymers causes the maximal arc voltage increase 16.2% with POM and 18.9% with PA6 in this case and causes the average arc velocity increase 15.8% with POM and 21.1% with PA6 in this case. The experiments are also carried out to study the influence of polymers on arc voltage and arc root position in the arc chamber during arc motion. The experimental results prove the validity of the numerical investigation.