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Design Of Analog Cmos Integrated Circuits

The recent outbreak of COVID-19 has taken the world by surprise, forcing lockdowns and straining public health care systems COVID-19 is known to be a highly infectious virus, and infected individuals do not initially exhibit symptoms, while some remain asymptomatic Thus, a non-negligible fraction of the population can, at any given time, be a hidden source of transmissions In response, many governments have shown great interest in smartphone contact tracing apps that help automate the difficult task of tracing all recent contacts of newly identified infected individuals However, tracing apps have generated much discussion around their key attributes, including system architecture, data management, privacy, security, proximity estimation, and attack vulnerability In this article, we provide the first comprehensive review of these much-discussed tracing app attributes We also present an overview of many proposed tracing app examples, some of which have been deployed countrywide, and discuss the concerns users have reported regarding their usage We close by outlining potential research directions for next-generation app design, which would facilitate improved tracing and security performance, as well as wide adoption by the population at large

A Survey of COVID-19 Contact Tracing Apps

An accurate and reliable Indoor Positioning System (IPS) applicable to most indoor scenarios has been sought for many years. The number of technologies, techniques, and approaches in general used in IPS proposals is remarkable. Such diversity, coupled with the lack of strict and verifiable evaluations, leads to difficulties for appreciating the true value of most proposals. This paper provides a meta-review that performed a comprehensive compilation of 62 survey papers in the area of indoor positioning. The paper provides the reader with an introduction to IPS and the different technologies, techniques, and some methods commonly employed. The introduction is supported by consensus found in the selected surveys and referenced using them. Thus, the meta-review allows the reader to inspect the IPS current state at a glance and serve as a guide for the reader to easily find further details on each technology used in IPS. The analyses of the meta-review contributed with insights on the abundance and academic significance of published IPS proposals using the criterion of the number of citations. Moreover, 75 works are identified as relevant works in the research topic from a selection of about 4000 works cited in the analyzed surveys.

https://www.mdpi.com/1424-8220/19/20/4507/pdf

A Meta-Review of Indoor Positioning Systems.

A photoplethysmograph (PPG) is a simple medical device for monitoring blood flow and transportation of substances in the blood. It consists of a light source and a photodetector for measuring transmitted and reflected light signals. Clinically, PPGs are used to monitor the pulse rate, oxygen saturation, blood pressure, and blood vessel stiffness. Wearable unobtrusive PPG monitors are commercially available. Here, we review the principle issues and clinical applications of PPG for monitoring oxygen saturation.

/pdf/current-progress-of-photoplethysmography-and-spo2-for-health-56vkc6f4ek.pdf

Current progress of photoplethysmography and SPO2 for health monitoring.

KEY POINTS
The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exceeded the capacity of many public health agencies to undertake traditional contact tracing. To address the limitations of traditional contact tracing, numerous governments — including those of Alberta in

/pdf/digital-contact-tracing-for-covid-19-ru774z3e4f.pdf

Digital contact tracing for COVID-19.

The Global Navigation Satellite System (GNSS) cannot achieve accurate positioning and navigation in the indoor environment Therefore, efficient indoor positioning technology has become a very active research topic Bluetooth beacon positioning is one of the most widely used technologies Because of the time-varying characteristics of the Bluetooth received signal strength indication (RSSI), traditional positioning algorithms have large ranging errors because they use fixed path loss models In this paper, we propose an RSSI real-time correction method based on Bluetooth gateway which is used to detect the RSSI fluctuations of surrounding Bluetooth nodes and upload them to the cloud server The terminal to be located collects the RSSIs of surrounding Bluetooth nodes, and then adjusts them by the RSSI fluctuation information stored on the server in real-time The adjusted RSSIs can be used for calculation and achieve smaller positioning error Moreover, it is difficult to accurately fit the RSSI distance model with the logarithmic distance loss model due to the complex electromagnetic environment in the room Therefore, the back propagation neural network optimized by particle swarm optimization (PSO-BPNN) is used to train the RSSI distance model to reduce the positioning error The experiment shows that the proposed method has better positioning accuracy than the traditional method

/pdf/indoor-positioning-algorithm-based-on-the-improved-rssi-3rkvc0t6k5.pdf

Indoor Positioning Algorithm Based on the Improved RSSI Distance Model.

In recent years, the increase of satellites and UAV (unmanned aerial vehicles) has multiplied the amount of remote sensing data available to people, but only a small part of the remote sensing data has been properly used; problems such as land planning, disaster management and resource monitoring still need to be solved. Buildings in remote sensing images have obvious positioning characteristics; thus, the detection of buildings can not only help the mapping and automatic updating of geographic information systems but also have guiding significance for the detection of other types of ground objects in remote sensing images. Aiming at the deficiency of traditional building remote sensing detection, an improved Faster R-CNN (region-based Convolutional Neural Network) algorithm was proposed in this paper, which adopts DRNet (Dense Residual Network) and RoI (Region of Interest) Align to utilize texture information and to solve the region mismatch problems. The experimental results showed that this method could reach 82.1% mAP (mean average precision) for the detection of landmark buildings, and the prediction box of building coordinates was relatively accurate, which improves the building detection results. Moreover, the recognition of buildings in a complex environment was also excellent.

An Optimized Faster R-CNN Method Based on DRNet and RoI Align for Building Detection in Remote Sensing Images

A lightweight method of data encryption in BANs using electrocardiogram signal

A logistic mapping-based encryption scheme for Wireless Body Area Networks

Reversible logic is a key technique for quantum computing so leading to low-power designs. However, current synthesis algorithms for reversible circuits are low efficiency and do not obtain optimized reversible circuits, so they are only applied to small logic functions. In this paper, we propose a new method based on positive Davio expansion to synthesize reversible circuits, which generates a positive Davio decision diagram for a logic function and transfers diagram nodes to reversible circuits. The algorithm has advantages of optimizing area and fast synthesis speed compared to BDD (Binary decision diagram) based and RM (Reed-Muller) based synthesis method, so it can be adapted for large functions.

Jinzhao Lin

Papers

Indoor Positioning Algorithm Based on the Improved RSSI Distance Model.

An Optimized Faster R-CNN Method Based on DRNet and RoI Align for Building Detection in Remote Sensing Images

A lightweight method of data encryption in BANs using electrocardiogram signal

A logistic mapping-based encryption scheme for Wireless Body Area Networks

Positive Davio-based synthesis algorithm for reversible logic