High-Performance Fingerprint Localization in Massive MIMO System

Location-based service (LBS) for both security and commercial use is becoming more and more important with the rise of 5G. Fingerprint localization (FL) is one of the most efficient positioning methods for both indoor and outdoor localization. However, the positioning time of previous research cannot achieve real-time requirement and the positioning error is meter level. In this paper, we concentrated on high-performance in massive multiple-in-multiple-out (MIMO) systems. Principal Component Analysis (PCA) is applied to reduce the dimension of fingerprint, so that the positioning time is about tens of milliseconds with lower storage. What’s more, a novel fingerprint called Angle Delay Fingerprint (ADF) is proposed. Simulation result of the positioning method based on ADF shows the positioning error is about 0.3 meter and the positioning time is about hundreds of milliseconds, which is much better than other previous known methods. (Foundation items: Social Development Projects of Jiangsu Science and Technology Department (No.BE2018704).)

Comparison of different approaches to combined spinal epidural anesthesia (CSEA) under the guidance of ultrasound in cesarean delivery of obese patients: a randomized controlled trial

Background Combined spinal epidural anesthesia (CSEA) is commonly performed in cesarean deliveries. However, it is difficult to perform in obese parturients because of positioning challenges. The aim of this study was to compare the effect of different approaches to CSEA under the guidance of ultrasound. Methods One hundred obese patients (BMI ≥ 30 kg/m2) who underwent elective cesarean section were randomly enrolled. Patients were assigned to a median approach group and a paramedian approach group randomly. Clinical characteristics were compared between groups. First-attempt success rate, the median positioning time and total operation time, ultrasonic predicted anesthesia puncture depth, actual puncture depth, anesthesia adverse reactions, complications after anesthesia, and patients’ satisfaction with the epidural puncture were recorded. Results The first-attempt success rate was significantly different between the two groups [92% (46/50) vs. 76% (38/50), P = 0.029]. The median positioning time and total operation time in the paramedian approach group were higher than those in the median approach group (227.7 s vs. 201.6 s, P = 0.037; 251.3 s vs. 247.4 s, P = 0.145). The incidence of postanesthesia complications in the paramedian approach group was significantly lower than that in the median approach group (2% vs. 12%, P = 0.026), and patient satisfaction was higher in the paramedian approach group than in the median approach group (P = 0.032). Conclusion The ultrasound-guided paramedian approach for CSEA is time-consuming, but it can effectively improve the success rate of the first puncture, reduce the incidence of anesthesia-related adverse reactions, and improve patient satisfaction. Trial registration: This study was registered with the Chinese Clinical Trial Registry (ChiCTR1900024722) on July 24, 2019

The QR code intelligent positioning system of the LBS cloud platform in the Internet of things environment

Aiming at the problems of long positioning time and poor positioning accuracy in traditional positioning systems, a WeChat applet QR code area positioning system based on the LBS cloud platform is proposed and designed. The overall architecture of the system is divided into three parts: LBS cloud service, central data processing, and QR code positioning terminal for small programs. The hardware is designed from the server-side module, processor and positioning module to provide a basis for system construction. In the software design, the WeChat applet QR code area image is collected, the image edge features are enhanced and filtered, the positioning target is determined according to the processed image edge features, and the WeChat applet QR code area positioning system design is completed. The experimental results show that the positioning time of the system is equivalent to 50% of the traditional system, and the positioning accuracy is always maintained above 99.5%, which has significant advantages.

Cost-Efficient LEO Navigation Augmentation Constellation Design under a Constrained Deployment Approach

The advantages of the Low Earth Orbit (LEO) satellite include low-latency communications, shorter positioning time, higher positioning accuracy, and lower launching, building, and maintenance costs. Thus, the introduction of LEO satellite constellation as a regional navigation augmentation system for the current navigation constellations is studied in this paper. To achieve the navigation performance requirement with the least system cost, a synthetic approach is presented to design and deploy a cost-efficient LEO navigation augmentation constellation over 108 key cities. To achieve lower construction costs, the constellation is designed to be deployed by constrained piggyback launches, which brings additional complexity to the constellation design. Two optimization models with discrete and continuous performance indices are established. They are solved by the genetic algorithm and differential evolution algorithm, and both Walker and Flower constellations are adopted. Results for 77 and 70 satellites are obtained. During the construction phase, a synthesis procedure containing five impulses is proposed by utilizing natural drift under J 2 perturbation. This work presents a method for designing the optimal LEO navigation constellation under a constraint deployment approach with the lowest construction cost and a strategy to deploy the constellation economically.

Effects of Canopy and Multi-Epoch Observations on Single-Point Positioning Errors of a GNSS in Coniferous and Broadleaved Forests

Global navigation satellite systems (GNSS) can quickly, efficiently, and accurately provide precise coordinates of points, lines, and surface elements, plus complete surveys and determine various boundary lines in forest investigations and management. The system has become a powerful tool for dynamic forest resource investigations and monitoring. GNSS technology plays a unique and important role in estimating timber volume, calculating timber cutting area, and determining the location of virgin forest roads and individual trees in forests. In this study, we quantitatively analyzed the influence of crown size and observation time on the single-point positioning accuracy of GNSS receivers for different forest types. The GNSS located single points for different forest types and crown sizes, enabling the collection of data. The locating time for each tree was more than 10 min. Statistical methods were used to analyze the positioning accuracy of multi-epoch data, and a model was developed to estimate the maximum positioning errors under different forest conditions in a certain positioning time. The results showed that for a continuous positioning time of approximately 10 min, the maximum positioning accuracies in coniferous and broadleaf forests were obtained, which were 12.13 and 15.11 m, respectively. The size of a single canopy had no obvious influence on the single-point positioning error of the GNSS, and canopy density was proven to be closely related to the positioning accuracy of a GNSS. The determination coefficients (R2) in the regression analysis of the general model, coniferous forest model, and broadleaved forest model that were developed in this study were 0.579, 0.701, and 0.544, respectively. These results indicated that the model could effectively predict the maximum positioning error in a certain period of time under different forest types and crown conditions at middle altitudes, which has important guiding significance for forest resource inventories and precise forest management.

Research on the Positioning Method of Single-Phase to Earth Fault in Distributed Distribution Network

The existing high-density distributed distribution network single-phase earth fault interval location method has the disadvantage of long positioning time. Hence, a single-phase earth fault interval positioning method for high-density distributed distribution network is proposed to solve this problem. In order to accurately locate the single-phase earth fault interval of distribution network, zero-order equivalent model of distribution network is built at first. Next the clustering algorithm is used to extract the single-phase earth fault characteristics, while the single-phase earth fault phase current increment is calculated by using the analysis method to obtain the single-phase earth fault phase current increment law. Then a fault-maximum interval T-shaped structure is built to divide the potential fault interval. Finally, the S-transformation is applied to accurately locate the single-phase earth fault interval, and the localization of the single-phase earth fault interval of the high-density distributed distribution network is achieved. The experimental results show that comparing with the existing high-density distributed distribution network single-phase earth fault interval positioning method, the proposed high-density distributed distribution network single-phase earth fault interval positioning method dramatically reduces the positioning time. It is fully explained that the proposed method in this article has a better positioning effect.

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

Objective To analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method. Materials and methods One hundred twenty-seven adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time, and off-center distance of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups. Results The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP 1.56 cm ± 0.83 vs. MP 4.05 cm ± 2.40, p < 0.001) and higher proportion of positioning accuracy (AP 99% vs. MP 92%), resulting in 16% radiation dose reduction (AP 6.1 mSv ± 1.3 vs. MP 7.3 mSv ± 1.2, p < 0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas. Conclusion The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose and optimizing imaging workflow and image quality in imaging the chest. Key Points • The AI-based automatic positioning (AP) operation was successful for all patients in our study. • AP method reduced the total positioning time by 28% compared with the manual positioning (MP). • AP method had less patient off-center distance and higher proportion of positioning accuracy than MP method, resulting in 16% radiation dose reduction and 9% image noise reduction in erector spinae.

A comparison between manual and artificial intelligence-based automatic positioning in CT imaging for COVID-19 patients

Objective: To analyze and compare the imaging workflow, radiation dose and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method. Materials and Methods: 127 adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time and off-center distance, of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups.Results: The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP:1.56cm±0.83 vs. MP: 4.05cm±2.40, p<0.001) and higher proportion of positioning accuracy (AP: 99% vs. MP: 92%), resulted in 16% radiation dose reduction (AP: 6.1mSv±1.3 vs. MP: 7.3mSv±1.2, p<0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas.Conclusion: The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose, optimizing imaging workflow and image quality in imaging the chest. This technique has important added clinical value in imaging COVID-19 patients to reduce the cross-infection risks.

Artificial intelligence-based patient positioning for faster, more accurate and efficient CT imaging for COVID-19 patients

Objective: To analyze and compare the imaging workflow, radiation dose and image quality for COVID-19 patients examined using either the conventional manual positioning method or an AI-based positioning method. Materials and Methods: 127 adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based positioning method (AP group) for the follow-up scan. Radiation dose, patient off-center distance, examination and positioning time of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups.Results: The AP group reduced the total positioning time and examination time by 28% and 8%, respectively compared with the MP group. Compared with the MP group, AP group had significantly less patient off-center distance (AP:1.56cm ± 0.83 vs. MP: 4.05cm ± 2.40, p<0.001) and higher proportion of positioning accuracy (AP: 99% vs. MP: 92%), resulted in 16% radiation dose reduction (AP: 6.1mSv ± 1.3 vs. MP: 7.3mSv ± 1.2, p<0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas.Conclusion: The AI-based positioning and centering in CT imaging is a promising new technique for reducing radiation dose, optimizing imaging workflow and image quality in imaging the chest. This technique has important added clinical value in imaging COVID-19 patients to reduce the cross-infection risks.

Ultrasound-Guided Single-Penetration Block for Sciatic and Saphenous Nerve Versus The Traditional Double Penetration Popliteal- Sciatic/Saphenous Technique for Leg and Foot Surgery

Background A new approach is described to blocking the sciatic and saphenous nerves in the proximal thigh (level of the lesser trochanter or immediately below) using a single-penetration technique. The popliteal-sciatic approach necessitates repositioning of the leg exposing the popliteal fossa and an extra injection for the saphenous nerve (SAN) block at the midthigh level. Aim of the Study The aim of this work is to compare between the new single-penetration block technique for block of the SCN and SAN at proximal thigh and the traditional popliteal sciatic nerve block at popliteal fossa with saphenous nerve block at adductor canal technique for leg and foot surgery. Subjects and Methods This prospective single blinded randomized parallel group study was conducted to compare between the ultrasound guided single penetration block technique for sciatic and saphenous nerve at proximal thigh to the traditional popliteal sciatic nerve block at popliteal fossa and saphenous block at adductor canal. Results Performance time was significantly faster with the single penetration technique median time 6.33 minutes (range, 3-10 minutes) versus 12.57 minutes (range from 8-20 minutes) (P &lt; 0.001), respectively Positioning time was also significantly shorter with the single penetration block technique compared to the traditional block combination technique that is median time 0 minutes (range, 0-0 minutes) versus median time 5.78 minutes (range 3-10 minutes) (P &lt; 0.001), respectively. No other statistically significant differences were recorded. Conclusions The single penetration block resulted in significantly faster performance time and reduced positioning time with statistically equal efficacy in relation to pain assessment, nausea, meperdin demand, dermatomal anesthesia, and motor blockade. The single penetration block is statistically an equally effective alternative to the traditional popliteal-sciatic/saphenous block combination for leg and foot surgery, but it is faster, requires only 1 skin penetration, and does not require repositioning of the leg.