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Irony detection aims to analyze and identify language expressions containing irony in texts, which can assist text sentiment analysis and opinion mining. Hyperbolic expressions are the unique language characteristics in Chinese ironic texts that often highlight the critics’ ironic intentions. Existing methods of irony domain lexicon construction ignore the hyperbolic expressions in the construction process, resulting in incomplete semantic information contained in the lexicon. Considering this problem, this paper proposes a method for constructing a hyperbolic representation lexicon to mine the language feature and improve the accuracy of irony detection. Firstly, we select the candidate words and word pairs of hyperbolic representation by Word2Vec combined with the K-means++ algorithm. Then, the information entropy is calculated to measure the correlation between candidate words and texts, so the seed word set with a high correlation with texts is obtained. Finally, we expand the seed word set using WoBERT to capture the text’s deep semantic information. Thus, the generalization ability of the hyperbolic representation lexicon is improved. The experimental results show that combining the lexicon constructed in this paper can effectively mine the language features of ironic texts, thereby improving the accuracy of irony detection. The experimental indicators Acc and F1-score have an average improvement of about 2.38% and 2.29%, respectively.

The Moon-based ground penetrating radar (GPR) carried by the Yutu rover performed in-situ radar measurements to explore extraterrestrial objects, which provides an unprecedented opportunity to study the shallow subsurface structure of the Moon and its internal resources. Exploiting lunar resources might be one of the solutions to the Earth's energy shortage in the future. In this article, first, the thickness distribution of the lunar regolith at the Chang'E-3 landing site is derived using the high-frequency Yutu radar observation data. Second, the surface concentration of helium-3 is determined based on the surface TiO$_{2}$ content of the lunar regolith. Finally, the reservoir of helium-3 resources in the lunar regolith is estimated. Our result suggests that the helium-3 reservoir along the Yutu rover traveling route from the navigation points N105 to N208 ($\sim$445 m$^{2}$) is $\sim$37–51 g, and its helium-3 content per unit area is $\sim$0.083–0.114 g/m${^{2}}$, which is at least five times higher than that of the global average. Currently, the nuclear fusion experiment is facing a severe shortage of tritium fuel. We discuss the possibility of replacing it with lunar helium-3 as the fuel for nuclear fusion. Meanwhile, we also suggest that the Chang'E-3 landing area can be a potential site selection for the exploitation of the lunar helium-3 in the future. Our results will provide a valuable reference to evaluate the economics and feasibility of mining in-situ helium-3 resources on the Moon.

Compared with AC microgrid, DC microgrid has attracted more and more attention due to their high reliability and simple control. In this paper, we analyze the existence and stability of equilibrium of DC microgrid under distributed control. Firstly, the power-flow equation of the DC microgrid with $n$ DGs and $m$ CPLs is built. On this basis, under the limitation of currents of DGs, the sufficient solvability conditions are obtained based on Brouwer’s fixed-point theorem. Secondly, we build the small-signal model to forecast the system qualitative behavior around equilibrium. The eigenvalue analysis based on inertial theorem provides the analysis basis for system stability, then we obtain the robust stability condition based on the properties of a special matrix. The obtained stability conditions provide a reference for establishing a stable DC microgrid. Lastly, simulation results verify the correctness of the proposed theorems.

This study introduces a novel Parallel Hybrid Island architecture which shows a parallel way to combine different meta-heuristic algorithms by using the island model as the base. The corresponding hybrid algorithm is called Parallel Hybrid Island Metaheuristic Algorithms (PHIMA). The hybrid parallel structure exploits the characteristics of the individual metaheuristic algorithms to boost robustness and diversity. Island Genetic Algorithm has been combined with Particle Swarm Optimization and Fireworks Algorithm to build three different PHIMA algorithms: PSO-GA (PHIMA-PGA), FWA-GA (PHIMA-FGA) and FWA-PSO-GA (PHIMA-FPGA). Further, another implementational variation known as “co-evolution” is applied to the sub-GA islands of PHIMA-FPGA to improve the performance on multi-modal high-dimensional problems. This variation is referred to as PHIMA-FPGA-Co. Each PHIMA Algorithm exhibits different advantages and characteristics, and the parallel hybridization using the island model is found to improve robustness and population diversity. The performances of the four new algorithms are compared with each other and that of the traditional Island GAs and all four proposed PHIMA algorithms show better result quality.

The credibility of information is known as a major cause of a wide range of issues, such as: altered product information in food supply chains; fake transactions on E-commerce platforms; lengthy claim settlement time in agricultural insurance; and costly borrowings in agricultural financing. For a more specific example in food supply chains, end customers want to check the product information, but either doubt the authenticity of information, or simply do not have access to the information. The reason is that upstream suppliers and downstream retailers are often reluctant to share data, fearing privacy loss or business secret leakage. The consequence is that regulatory departments may face enormous challenges to identify accurate contamination sources, if there is scarce information or falsely recorded information at any stage of the food supply chain. In this paper, we focus on four common scenarios demanding information credibility in the agricultural supply chain: product traceability, E-commerce platforms, agricultural insurance, and agricultural financing. We review some high-profile smart credibility applications with emphasis on how blockchain related technologies can provide the information credibility by examining extant issues and relevant frameworks.

The wireless power terminals are deployed in harsh public places and lack strict control, facing security problems. Thus, they are faced with security problems such as illegal and counterfeit terminal access, unlawful control of connected terminals, etc. The intrusion detection system based on machine learning and artificial intelligence significantly improve the terminal side’s abnormal detection capacity. In this article, we aim at identifying the abnormal behavior of wireless power terminals based on a double Hidden Markov Model (HMM), which solves the computational complexity problem caused by high dimensions in intrusion detection systems using a single HMM. The lower-layer HMM is used to identify the discrete single network abnormal behavior. Simultaneously, the upper-layer can obtain more extended period attack behavior in multiple independent abnormal events identified by the low-level. The experiment results indicate that the intrusion detection system using proposed double HMM can effectively detect the terminal’s abnormal behavior and identify the network attack behavior for an extended period.

On the road of CMOS device continuously scaling, there are lots of challenges regarding the device structure and material engineering. GaN channel has recently been used in MOSFETs and achieved excellent performance. In this paper, we study a novel embedded gate GaN nanotube field effect transistor of 5 nm gate length with ION/IOFF as high as 106, and subthreshold swing (SS) as small as 64 mV/dec using Sentaurus TCAD simulation. The device can effectively improve subthreshold characteristics due to the GaN channel and embedded gate design. Compared with Si nanotube FET and GaN nanowire FET, GaN embedded nanotube FET exhibits low SS and high ION/IOFF at the same channel thickness. GaN embedded nanotube FET has also been determined to superior temperature adaptability and performs better in terms of threshold voltage and subthreshold characteristics compared to Si nanotube FET at the same temperature. In addition, we investigated the impact of different lengths and thicknesses of the embedded gate on the subthreshold characteristics. As the length and thickness of the embedded gate are increased, SS and ION/IOFF are improved. This excellent electrical performance demonstrates the possibility of GaN as a channel material in MOSFETs and embedded gate as an effective design to improve subthreshold characteristics, opening a new way for continued device scaling.

Consensus-based estimators have been applied in the state estimation for cooperative multi-sensor systems, and most of current studies are for the continuous-time or discrete-time case. With regards to some engineering applications, such as ballistic target tracking, it is more suitable to adopt the continuous-discrete state-space model to formulate a dynamic system, which can capture the evolution characteristics of this state process more accurately. This paper presents a novel consensus continuous-discrete Gaussian filtering (CCDGF) estimator. On the basis of strong Taylor approximation for continuous state, the estimator utilizes the fully symmetric interpolatory quadrature (FSIQ) rule to numerically resolve the first two moments of propagated Gaussian density. Then, the average consensus protocol is leveraged to iterate the local innovations of Gaussian filtering framework at each sensor. The consensus estimates with odd-degree accuracy can be obtained through sufficient exchanges of neighborhood information. Finally, it is demonstrated by simulation examples that the CCDGF estimator can achieve performance close to its centralized counterpart, and has higher tracking accuracy with the increase of quadrature degree.

As one of the emerging application areas of the corona discharge technique, rain enhancement induced by atmospheric air ionization has made a great breakthrough. Although natural rainfall modified by artificial ionization was successfully observed via the statistical data of field experiments, deficient efforts have been devoted to the research on the near-field effect of corona discharge on the evolution of water droplets around the discharge device. In this article, we studied the electrostatic effects of corona discharge on the spectrum and density evolution of water droplets in a 96-m3 cloud chamber. An interesting phenomenon was found that two different electrostatic effects appeared when various high voltages were applied on the corona electrode. In detail, the growth of droplets larger than 10 μm was detected once the applied high voltage exceeds the critical value (e.g. -80 kV in our discharge device), and this is attributed to the electrostatic induction effect. By contrast, a narrow droplet size spectrum and reduced density caused by the strong electrostatic precipitation effect were shown below this critical voltage. To figure out the mechanisms underlying these phenomena, the charging status of water droplets with various sizes, forces of charged droplets under various electric field strength, and collision kernels between droplets, are analyzed through theoretical calculations. Results show that the electric field plays a dominant role in the charging process of droplets and the acceleration of collision-coalescence between charged and neutral droplets, which results in the different electrostatic effects on the evolution of droplets. This article may provide some enlightenment to fog elimination in industrial application and cloud-seeding in atmospheric water resources comprehensive utilization.

The penetration of renewable energy generations, e.g., wind power, not only introduces the randomness and fluctuations into power system operations but also increases the possibilities of cybersecurity issues. Among them, false data injection attack (FDIA) can access and falsify the readings of smart meters, which would impede the functionalities of power systems. In this paper, we first set up an evaluation model to identify the set of high-risk lines by investigating the relationship between FDIA and wind power uncertainty. Then, for a power system with a high wind penetration, a tri-level preventive dispatch strategy is proposed to ensure the system security even under the worst-case of FDIA. It is demonstrated that the impacts of FDIA can cause more serious security issues as the wind penetration level increases. The effectiveness of the proposed tri-level preventive dispatch strategy in mitigating the FDIA caused overloading risk is validated using the IEEE 118-bus system.

This paper proposes a design method for high-isolation n-way power combiners based on 2n + 1 port mode networks. The scattering matrix of a 2n + 1 port mode network is obtained by rigorously deriving the voltage and current relations. Following the proposed method, a compact four-way coaxial power combiner based on a nine-port mode network is designed and fabricated. Measurements show that from 7.8 to 10.3 GHz, the return losses of the input and output ports are better than -18 and -21 dB, respectively, the isolation levels between the input ports are higher than 21 dB, the insertion loss for power combination is less than 0.2 dB, and the amplitude and phase imbalances of the power combiner are less than approximately 0.15 dB and 2°, respectively. The simulated results agree well with the measured results. Moreover, the combiner has compact cross-sectional dimensions of 1.2λ × 1.2λ. It is clear that the designed four-way power combiner is superior in terms of its compact cross-sectional dimensions, high degree of isolation, low return loss, low insertion loss, and output amplitude and phase imbalance, which make it well suited for solid-state power combination. In addition, the power combiner is easy to fabricate and assemble. The proposed method shows great potential for realizing multi-way power combination with high isolation, low return loss, and compact cross-sectional dimensions.

Hop-by-hop transport is promising in information-centric networking because of its adaptability to in-network caching and lossy environments. Mobility first transport protocol (MFTP), as a classical example, transports content chunks and waits for the retransmissions of the lost packets in each hop. However, due to its chunk-level reliability, the MFTP hops transport chunks in series rather than in parallel, causing significant longer end-to-end latency than that in transmission control protocol (TCP). To address this issue, we propose a novel hop-by-hop transport mechanism, R2T. In each hop, R2T guarantees the content reliability in packets rather than in chunks. R2T routers immediately forward all the received packets downstream so that the end-to-end latency can be remarkably decreased. With separated packet name space in global and local scale, R2T decouples the hop-by-hop reliability control and the end-to-end content transport, obtaining both performance advantages from MFTP and TCP. The evaluation results show that R2T has as low transport latency as TCP, yet keeps as high bandwidth usage as MFTP. Meanwhile, it is demonstrated that R2T does not suffer significant memory and energy consumption, achieving promising feasibility in real implementations.