University of Electronic Science and Technology of China

About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.

Low-Complexity Signal Detection for Generalized Spatial Modulation

Abstract: Generalized spatial modulation (GSM), in which only part of the transmit antennas are activated in each time slot, was recently proposed as a trade-off between spatial modulation (SM) and vertical Bell laboratories space-time (V-BLAST). Although the maximum likelihood (ML) detector is able to achieve the optimal performance, its exhaustive search leads to intractable computational complexity. In this letter, an efficient signal detection algorithm, termed ordered block minimum mean-squared error (OB-MMSE), is proposed for achieving near-ML performance with low complexity. On one hand, an ordering algorithm is proposed to sort the possible transmit antenna combinations (TACs). On the other hand, the possible signal vector for each ordered TAC is detected by block-MMSE equalization. Simulation results show that the proposed OB-MMSE detector provides similar performance to ML with near 80% reduction in complexity.

Anatase TiO2 nanocubes for fast and durable sodium ion battery anodes

Abstract: With the aim of advancing anatase TiO2 anodes for sodium ion batteries, crystalline titania nanocubes were employed and they delivered a gradually increasing capacity during the initial cycles, termed as an activation process The number of necessary discharge–charge loops for total activation is dependent on the galvanostatic current density (about 20 cycles at 02 C, or 90 cycles at 1 C) A percentage of Ti3+ was detected after the activation, indicating an amount of irreversibly trapped sodium ions in the lattice After the activation process, an excellent rate capability and outstanding cycling stability were presented The reversible capacity reached 174, 132, and 108 mA h g−1 at rates of 1 C, 5 C, and 10 C, respectively The capacity was sustained with a loss of less than 10% after 1000 discharge–charge cycles at a rate of 2 C or 10 C The superior battery performance achieved by the nanocubes is related to the encircled {100} facets that are more favorable for sodium ion attachment compared to the {001} and {101} facets, as supported by first-principles calculations From this work we can see the feasibility of optimizing electrode materials via rational surface structure construction based on theoretical calculations

DS-VIKOR: A New Multi-criteria Decision-Making Method for Supplier Selection

Abstract: How to select the optimal supplier is an open and important issue in supply chain management, which can be considered as a multi-criteria decision-making (MCDM) problem. The assessment of experts plays a very important role in the process of supplier selection, while their subjective judgment could produce unpredictable uncertainty. However, existing methods cannot represent and deal with the uncertainty effectively. Dempster–Shafer evidence theory (D–S theory) is widely used in uncertainty modeling, decision-making and conflicts management due to its advantages of handling uncertain information. The VIKOR method has a great advantage to handle MCDM problems with non-commensurable and even conflicting criteria, and to obtain the compromised optimal solution. In this paper, the DS-VIKOR method is proposed for supplier selection problem, which expends the VIKOR method by D–S theory. In the proposed method, the basic probability assignment is used to denote the assessment of domain experts for alternatives, Deng entropy weight-based method is defined and applied to determine the weights of multi-criteria, and VIKOR method is used to get the final ranking results. A numerical example for supplier selection is conducted to analyze and demonstrate the practicality and effectiveness of the proposed DS-VIKOR method.

Ship Detection in Large-Scale SAR Images Via Spatial Shuffle-Group Enhance Attention

Abstract: Ship target detection using large-scale synthetic aperture radar (SAR) images has important application in military and civilian fields. However, ship targets are difficult to distinguish from the surrounding background and many false alarms can occur due to the influence of land area. False alarms always occur with ship target detection because most of the area in large-scale SAR images are treated as background and clutter, and the ship targets are considered unevenly distributing small targets. To address these issues, a ship detection method in large-scale SAR images via CenterNet is proposed in this article. As an anchor-free method, CenterNet defines the target as a point, and the center point of the target is located through key point estimation, which can effectively avoid the missing detection of small targets. At the same time, the spatial shuffle-group enhance (SSE) attention module is introduced into CenterNet. Through SSE, the stronger semantic features are extracted while suppressing some noise to reduce false positives caused by inshore and inland interferences. The experiments on the public SAR-ship-data set show that the proposed method can detect all targets without missed detection with dense-docking targets. For the ship targets in large-scale SAR images from Sentinel 1, the proposed method can also detect targets near the shore and in the sea with high accuracy, which outperforms the methods like faster R-convolutional neural network (CNN), single-shot multibox detector (SSD), you only look once (YOLO), feature pyramid network (FPN), and their variations.