A novel fixed-frequency beam switchable dual-beam antenna array is presented, which consists five dual-beam leaky-wave antenna (LWA) elements designed on substrate integrated waveguide (SIW) and ...integrated together on a common substrate. The LWAs work on fundamental wave and -1th spatial harmonic wave simultaneously and excite two symmetrical radiation beams in forward and backward direction respectively. In order to realize beam switching, three voltage-driven radio frequency chip switches (CSW-RFs) are used and integrated behind the antenna aperture. Since the periodic slot in LWA causes open stopband at the operating frequency, so the staggered radius amplification of local vias in the via walls of SIW is performed to suppress the open stopband. In addition, electromagnetic band-gap (EBG) structures, capable of reducing coupling between neighboring antenna elements, are embedded in between LWAs. The proposed dual-beam antenna array with beam switching capability between ±35, ±45, ±55, ±65 and ±75 degrees at 28 GHz are simulated, fabricated and measured. Both analysis and measurement results show that the proposed antenna array exhibits an excellent performance, which can be used in fixed-frequency beam-switching millimeter wave communication.
Arbitrarily oriented object detection in remote sensing images is a challenging task. At present, most of the algorithms are dedicated to improving the detection accuracy, while ignoring the ...detection speed. In order to further improve the detection accuracy and provide a more efficient model for scenes that require real-time detection, we propose an improved YOLOv4-CSP network for rotating object detection in remote sensing images. There are mainly three contributions in our approach. First, we design a new bounding box regression loss function, which is distance and angle-intersection over union (DAIoU). This loss function is formed by adding a distance penalty term and an angle penalty term on the basis of intersection over union. It is suitable for arbitrarily oriented object detection networks. Second, we develop an adaptive angle setting method for anchors based on k-means clustering algorithm. This method can obtain representative angles for better representing the distribution of the angle set. By assigning representative angles to all anchors for training, it is beneficial to reduce the complexity of the network to adjust anchors to GT bounding boxes. Finally, we improve the YOLOV4-CSP network and make it suitable for detection scenarios based on rotated anchors by applying rotation transformations. We combine the above methods and use the final network to perform the detection task. The experimental results on three remote sensing datasets, i.e., HRSC2016, UCAS-AOD, and SSDD+, validate the effectiveness of our method. Comparison results with state-of-the-arts methods demonstrate that our method can be used to significantly improve the detection accuracy with a higher detection speed.
Shield tunneling activities inevitably pass through pile foundations at close distance in densely urban areas. Various studies have investigated the interaction between newly constructed tunnels and ...existing pile foundations. However, the influence of different construction sequences of twin paralleled shield tunneling on single long pile is seldom considered. A case was found in the project of Changsha Metro Line 5, where the twin paralleled tunnels were constructed near the Wanjiali Viaduct piles. A three-dimensional finite element model was established to analyze the pier settlement, ground surface settlement trough, and the vertical and horizontal displacement of pile under different construction sequences in layered soil. The results show that the adjacent pile and surrounding environment are affected substantially with the change of construction sequence of twin paralleled tunnels. The construction sequence of condition (b), in which the tunnel closer to the pile foundation is first constructed and then the tunnel farther away from the pile foundation is second constructed, can reduce the settlement of pier by 13.1%, the maximum surface settlement by 7.0%, the maximum vertical displacement of pile foundation by 7.9%, and the maximum horizontal displacement by 6.9%. The present findings can provide reference for similar projects.
In computer vision, convolutional neural networks (CNNs) obtain extremely striking recognition performance. However, in many CNNs there exists a great deal of parameter redundancy because of matrix ...kernels. To address this problem, we propose a novel model, namely, vector-kernel convolutional neural network (VeckerNet). In a VeckerNet, each convolutional layer can only use vector kernels of either size k × 1 or 1 × k. Compared to the popular models, e.g., AlexNet, VGG, ResNet and DenseNet, the VeckerNets obtain up to 20.8% relative performance improvement with the parameter reduction by 3 to 97%. Impressively, compared to the ResNets with the same depth, e.g., 44, 56, 101 and 110 layers, the VeckerNets obtain 0.57 to 1.4% relative performance improvement with a decrease of parameters by up to more than two-thirds. The experimental results indicate that the VeckerNets can retain good recognition performance while effectively reducing network parameters.
This study sought to investigate the vertical distribution pattern of the soil faunal community in a low-altitude mountain area. On 8 July 2022, a low hill was selected as the study area, and soil ...arthropods were collected through traps. The leaf litter, vegetation type, and distribution quantity of each sampling site were investigated while the soil faunae were collected. In addition, the soil’s physical and chemical parameters were measured. The results of a one-way ANOVA showed that there were significant differences (p < 0.05) in the soil properties, leaf litter, and plant quantities at different altitudes within the research area. A total of 1086 soil arthropods, belonging to five classes and ten orders, were collected during the study period. The dominant species of soil arthropods at different altitudes were significantly different. The dominant species in low-altitude areas were Armadillidium sp. and Aethus nigritus. However, Eupolyphaga sinensis and Philodromidae were the dominant species in high-altitude areas. The results of a non-metric multidimensional scaling (NMDS) analysis showed that the soil faunae at different altitudes were clustered into two communities: a high-altitude community and a low-altitude community. With the increase in altitude, the species richness of the soil arthropods gradually decreased, and their abundance showed a decreasing trend. A redundancy analysis (RDA) of the soil arthropods and environmental factors showed that soil moisture (p < 0.01), pH (p < 0.01) and defoliation (p < 0.05) had significant effects on the distribution of the soil fauna. The results of a Pearson correlation analysis indicated that different environmental factors had interactive effects on the distribution of the soil arthropods. The quantity and species richness of the soil arthropods in different sample lines were tested using a variance analysis. The results showed that there were significantly smaller quantities of soil arthropods in the sampling line closer to the trekking ladder. This indicates that human tourism, namely mountaineering activities, had a direct impact on the soil fauna. This study can provide a reference for and data support in the development of biodiversity conservation measures for forest parks in low mountain areas.
Two-dimensional hidden Markov model (2-D HMM) is an extension of 1-D HMM to 2-D, it provides a reasonable statistical method to model matrix data. This paper presents some new strict definitions of ...2-D HMM and proves the equivalence between them, and gives a study of the three basic problems for 2-D HMM, namely, probability evaluation, optimal state matrix and parameter estimation. By using the ideal that the sequences of states on columns or rows of a 2-D HMM can be seen as states of a 1-D HMM, several new formulae solving these problems are theoretically derived and further demonstrated by computer simulations.
Shield tunnels will inevitably pass through viaduct piles at a close distance due to the extensive construction of subways and viaducts in the city. In order to understand the influence of shield ...tunneling on the deformation of existing pile foundation and grouting protection measures, based on an engineering case, Changsha Metro Line 5 (from South Gaoqiao station to Guitang station), a three-dimensional finite element model was established to analyze the deformation of bridge pile using grouting protection wall with different depths and shapes when the shield tunnel is under construction. The analytical results indicate that the grouting protection wall can effectively reduce the pile displacement; especially the grouting depth is 3 m below the bottom of the tunnel. Moreover, the L-shaped grouting protection wall can effectively reduce the longitudinal displacement of the piles. The present findings may provide a reference for the design and construction of shield tunnels passing through viaduct piles.
A new kind of smart antenna capable of automatically switching its main beam to track a moving target is presented. The antenna, which is suitable for mobile communication in long straight spaces, ...such as railways or highways, integrates a sensing element, signal processing element, and radiating element. The sensing element works based on a frequency-modulated continuous wave and delivers a beat frequency signal containing environmental information to the signal processing element, which is used to control the excitation of the radiating element. To verify the efficiency of the proposed antenna, a prototype is fabricated and implemented in a real corridor scenario. Furthermore, the error vector magnitude (EVM) along the test path is investigated to evaluate the system performance when using the proposed antenna. The results show that this kind of smart antenna is capable of improving mobile communication quality and decreasing energy consumption. Therefore, it is a promising candidate for mobile communication.
In this letter, a novel dual-beam and tri-band leaky-wave antenna (LWA) based on substrate integrated waveguide (SIW) structure is proposed, which has the capability of wide beam scanning range ...including broadside direction. The antenna consists of two kinds of periodic structures which can excite two -1st spatial harmonic waves and result in two radiation beams simultaneously. Through theoretical dispersion diagram analysis of the unit cells of two periodic structures and by applying the techniques of impedance-matching and reflection-cancelling, the open-stopbands at broadside are suppressed. Then the main beam of the proposed LWA can scan from backward to forward through broadside when frequency changes. Moreover, a tri-band application can be achieved in the dual-beam antenna by optimization of the second periodic structure. The measured results validate that the proposed SIW LWA has three operating frequency bands. In band 1 from 8.6 to 9.2 GHz, there is one beam scanning from 42° to 71° in the forward, in band 2 from 10 to 12 GHz, there is one beam scanning from -40° to 4° in the backward, and in band 3 from 12.5 to 15 GHz, there is a dual-beam scanning from -55° to 54° including broadside direction, which show good agreements with the simulated results.
SMOTE is a well-known oversampling method for learning on imbalanced datasets. However, it has the risk of introducing noisy instances and overfitting problems. In order to improve its performance, ...this paper proposes an oversampling method called SMOTE-COF, which is an improvement of SMOTE based on center offset factor. The SMOTE-COF method first removes noisy samples, then computes center offset factor to select sparsely distributed minority class samples. Furthermore, these samples are used to generate new minority class samples with other minority class instances distributed in the same sub-cluster by SMOTE. Comparative experiments on one simulated dataset and fourteen UCI datasets provide evidence that the SMOTE-COF can effectively reduce noisy samples, generate better minority classes, and improve classification performance for imbalanced datasets.
•SSMOTE-COF is an improvement of SMOTE based on center offset factor.•SMOTE-COF computes center offset factor to select sparsely distributed minority class samples.•Sparse samples generate new samples with other minority class instances distributed in the same sub-cluster by SMOTE.•SMOTE-COF can generate better minority classes, and improve classification performance for imbalanced datasets.
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