An Performance Study for Sectorised Antenna based Doppler Diversity in High-Speed Railway Communications

The wireless channel of High-Speed Railway communication system is rapidly time-varying. The orthogonal frequency division multiplexing transmitting over this channel will be exposed to the intercarrier interference caused by large Doppler spread. The sectorised antenna can be employed for Doppler mitigation and obtaining Doppler diversity gain. In this paper the performance of this directional antenna is analyzed. The preferable partition scheme for the omnidirectional antenna and the optimal Doppler compensation frequency are addressed firstly. And the uncorrelated property of the signal received from the different sectorised antennas is demonstrated originally which can be utilized for Doppler diversity gain. Finally, it is proved by the simulation results that this architecture will allows us to achieve remarkable performance under high mobility conditions

Investigation of Shadowing Effects in Typical Propagation Scenarios for High Speed Railway at 2350 MHz

Based on realistic measurements in China, shadowing characteristics at the frequency of 2350 MHz were investigated in typical High-Speed Railway environments. After confirming that the measured shadowing satisfies wide-sense stationarity (assessed via the reverse arrangement test method), we quantify the shadowing correlation. Three types of correlation models are compared for the shadowing characterization, and the Normalized Mean Square Error is used to determine the best matching model: a single decaying exponential function. Decorrelation distances were found to be 11.9 m, 17.7 m, and 8.3 m in our three HSR scenarios, respectively. The results should be useful for the evaluation and verification of wireless communication in High-Speed Railway scenarios

Structural and Functional Analysis of Validoxylamine A 7′-phosphate Synthase ValL Involved in Validamycin A Biosynthesis

Validamycin A (Val-A) is an effective antifungal agent widely used in Asian countries as crop protectant. Validoxylamine A, the core structure and intermediate of Val-A, consists of two C7-cyclitol units connected by a rare C-N bond. In the Val-A biosynthetic gene cluster in Streptomyces hygroscopicus 5008, the ORF valL was initially annotated as a validoxylamine A 7′-phosphate(V7P) synthase, whose encoded 497-aa protein shows high similarity with trehalose 6-phosphate(T6P) synthase. Gene inactivation of valL abolished both validoxylamine A and validamycin A productivity, and complementation with a cloned valL recovered 10% production of the wild-type in the mutant, indicating the involvement of ValL in validoxylamine A biosynthesis. Also we determined the structures of ValL and ValL/trehalose complex. The structural data indicates that ValL adopts the typical fold of GT-B protein family, featuring two Rossmann-fold domains and an active site at domain junction. The residues in the active site are arranged in a manner homologous to that of Escherichia coli (E.coli) T6P synthase OtsA. However, a significant discrepancy is found in the active-site loop region. Also noticeable structural variance is found around the active site entrance in the apo ValL structure while the region takes an ordered configuration upon binding of product analog trehalose. Furthermore, the modeling of V7P in the active site of ValL suggests that ValL might have a similar SNi-like mechanism as OtsA

A Two-Stage Method for Online Signature Verification Using Shape Contexts and Function Features

As a behavioral biometric trait, an online signature is extensively used to verify a person’s identity in many applications. In this paper, we present a method using shape contexts and function features as well as a two-stage strategy for accurate online signature verification. Specifically, in the first stage, features of shape contexts are extracted from the input and classification is made based on distance metric. Only the inputs passing by the first stage are represented by a set of function features and verified. To improve the matching accuracy and efficiency, we propose shape context-dynamic time warping (SC-DTW) to compare the test signature with the enrolled reference ones based on the extracted function features. Then, classification based on interval-valued symbolic representation is employed to decide if the test signature is a genuine one. The proposed method is evaluated on SVC2004 Task 2 achieving an Equal Error Rate of 2.39% which is competitive to the state-of-the-art approaches. The experiment results demonstrate the effectiveness of the proposed method

Probe Sector Matching for Freehand 3D Ultrasound Reconstruction

A 3D ultrasound image reconstruction technique, named probe sector matching (PSM), is proposed in this paper for a freehand linear array ultrasound probe equipped with multiple sensors, providing the position and attitude of the transducer and the pressure between the transducer and the target surface. The proposed PSM method includes three main steps. First, the imaging target and the working range of the probe are set to be the center and the radius of the imaging field of view, respectively. To reconstruct a 3D volume, the positions of all necessary probe sectors are pre-calculated inversely to form a sector database. Second, 2D cross-section probe sectors with the corresponding optical positioning, attitude and pressure information are collected when the ultrasound probe is moving around the imaging target. Last, an improved 3D Hough transform is used to match the plane of the current probe sector to the existing sector images in the sector database. After all pre-calculated probe sectors are acquired and matched into the 3D space defined by the sector database, a 3D ultrasound reconstruction is completed. The PSM is validated through two experiments: a virtual simulation using a numerical model and a lab experiment using a real physical model. The experimental results show that the PSM effectively reduces the errors caused by changes in the target position due to the uneven surface pressure or the inhomogeneity of the transmission media. We conclude that the PSM proposed in this study may help to design a lightweight, inexpensive and flexible ultrasound device with accurate 3D imaging capacity

A Freehand 3D Ultrasound Reconstruction Method Based on Deep Learning

In the medical field, 3D ultrasound reconstruction can visualize the internal structure of patients, which is very important for doctors to carry out correct analyses and diagnoses. Furthermore, medical 3D ultrasound images have been widely used in clinical disease diagnosis because they can more intuitively display the characteristics and spatial location information of the target. The traditional way to obtain 3D ultrasonic images is to use a 3D ultrasonic probe directly. Although freehand 3D ultrasound reconstruction is still in the research stage, a lot of research has recently been conducted on the freehand ultrasound reconstruction method based on wireless ultrasonic probe. In this paper, a wireless linear array probe is used to build a freehand acousto-optic positioning 3D ultrasonic imaging system. B-scan is considered the brightness scan. It is used for producing a 2D cross-section of the eye and its orbit. This system is used to collect and construct multiple 2D B-scans datasets for experiments. According to the experimental results, a freehand 3D ultrasonic reconstruction method based on depth learning is proposed, which is called sequence prediction reconstruction based on acoustic optical localization (SPRAO). SPRAO is an ultrasound reconstruction system which cannot be put into medical clinical use now. Compared with 3D reconstruction using a 3D ultrasound probe, SPRAO not only has a controllable scanning area, but also has a low cost. SPRAO solves some of the problems in the existing algorithms. Firstly, a 60 frames per second (FPS) B-scan sequence can be synthesized using a 12 FPS wireless ultrasonic probe through 2–3 acquisitions. It not only effectively reduces the requirement for the output frame rate of the ultrasonic probe, but also increases the moving speed of the wireless probe. Secondly, SPRAO analyzes the B-scans through speckle decorrelation to calibrate the acousto-optic auxiliary positioning information, while other algorithms have no solution to the cumulative error of the external auxiliary positioning device. Finally, long short-term memory (LSTM) is used to predict the spatial position and attitude of B-scans, and the calculation of pose deviation and speckle decorrelation is integrated into a 3D convolutional neural network (3DCNN). Prepare for real-time 3D reconstruction under the premise of accurate spatial pose of B-scans. At the end of this paper, SPRAO is compared with linear motion, IMU, speckle decorrelation, CNN and other methods. From the experimental results, it can be observed that the spatial pose deviation of B-scans output using SPRAO is the best of these methods

ImDeeplabV3plus with instance selective whitening loss in domain generalization semantic segmentation

Abstract Semantic segmentation is a classical problem in computer vision, which is important in the field of autonomous driving. Although significant progress has been achieved in semantic segmentation, its generalization ability to unknown domains is still challenging. To effectively solve this problem, a semantic segmentation method ImDeeplabV3plus with instance selective whitening loss is proposed in this paper. DeeplabV3plus is selected as the baseline. In order to enhance the representation of the region of interest, the coordinate attention (CA) mechanism is added. To better integrate multiple low‐level features, the adaptively spatial feature fusion (ASFF) is employed to adaptively learn the importance of features at different levels for each location. For preferably coping with the domain changes, an instance selective whitening (ISW) loss is introduced in the early stage of the backbone. The model is trained with the Cityscapes dataset and then applied to the unknown domain RobotCar dataset. Compared with DeeplabV3plus, the authors’ ImDeeplabV3plus model shows 1.29% mIoU improvement. When ISW loss is added, 2.08% improvement in mIoU is achieved compared with ImDeeplabV3plus. Experimental results show that the proposed method is simple and improves the domain generalization ability

Background Modeling Method Based on 3D Shape Reconstruction Technology

In this research, we present a novel dynamic background modeling method based on reconstructed 3D shapes, which can solve background modeling problems of multi-camera in real-time. While 3D shape reconstruction is a popular technology widely used for detecting, tracking or identifying various objects, little effort has been made in applying this useful method to background subtraction. In this work we propose an approach to using 3D shape reconstruction technology to develop a novel decision making mechanism for background image updating. This 3D shape reconstruction based background subtraction method is adaptive to changes in illumination, capable of handling sudden illumination changes as well as complex dynamic scenes efficiently. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.238