Radar networks: A review of features and challenges

Networks of multiple radars are typically used for improving the coverage and tracking accuracy. Recently, such networks have facilitated deployment of commercial radars for civilian applications such as healthcare, gesture recognition, home security, and autonomous automobiles. They exploit advanced signal processing techniques together with efficient data fusion methods in order to yield high performance of event detection and tracking. This paper reviews outstanding features of radar networks, their challenges, and their state-of-the-art solutions from the perspective of signal processing. Each discussed subject can be evolved as a hot research topic.Comment: To appear soon in Information Fusio

Design and Implementation of a High Bit Rate HDLC Transceiver Based on a Modified MT8952B Controller

Abstract: To transmit and receive data over any network successfully, a protocol is required to manage the flow. High-level Data Link Control (HDLC) protocol is defined in Layer 2 of OSI model and is one of the most commonly used layer 2 protocols. HDLC supports both full-duplex and halfduplex data transfer. In addition, it offers error control and flow control. Using a modified MT8952B controller design, the current research presents a new method for implementing an ultra high bit rate HDLC Controller that is compatible with ST-BUS format using Xilinx Virtex FPGA as the target technology using VHDL for implementation. The HDLC Transceiver is used to transmit and receive the HDLC frames. Implementing the HDLC protocol transceiver in FPGA offers the flexibility, upgradeability and customization benefits of programmable logic and also reduces the total cost of every project which involves HDLC protocol controllers

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Automatic detection of quality soil spectra in an online vis-NIR soil sensor

The quality of online visible and near infrared (vis-NIR) soil spectra can be deteriorated by interferences of ambient light, and debris e.g., stones, roots or plant residues among others, which considerably reduces the accuracy of the predictions. Filtering of very noisy and non-soil spectra from good-quality soil spectra needs to be performed prior the modelling. Nevertheless, manual filtering of the large amount of vis-NIR online measurement is a laborious and time-consuming task. This study was conducted to develop an automatic filtering system of very noisy and non-soil spectra. Soil and non-soil spectra obtained during online vis-NIR measurements in four commercial fields in Flanders, Belgium were used to build two databases. The main difference in the databases is that flat spectra, mostly found in wet soil conditions, were considered as non-soil spectra in the first group and as soil spectra in the second group. Similarity algorithms [i.e., Pearson correlation, Spearman correlation, Euclidian distance, cosine distance and principal component analysis (PCA)] and machine learning algorithms (i.e., linear discriminant analysis, support vector machine and K-nearest neighbors) for spectra filtering using the two databases were evaluated and compared. Results suggest that the similarity algorithms were not successful to classify spectra into soil and non-soil classes for both groups, since the best prediction accuracy in cross validation achieved by the cosine distance algorithm was 76.11%. However, the machine learning algorithms provided high classification accuracies for both databases. For the former database, the best classification result of 98.5% in cross-validation and 98.6% in independent validation was obtained by using the k-nearest neighbor algorithm. While for the latter database, the best result was achieved by the support vector machine algorithm with a gaussian kernel obtaining 81.4% in cross-validation and 82.03% in independent validation. The best performing model was used to build a cleaning function to automatically pre-process and classify spectra into soil or non-soil classes. This automatic spectrum filtering system enables time saving and ensures only high-quality spectra are used for accurate online prediction of soil properties, necessary for sensor-based variable rate applications

Modernization in agricultural water distribution system for aquifer storage and recovery – A case study

High water consumption in the agricultural sector, population growth, urbanization, and industrialization have gradually turned groundwater into a quantitative and qualitative crisis. This study investigated aquifer storage and recovery (ASR) as the environmental effect of modernization projects in agricultural water distribution systems. For this purpose, a numerical model of the Qazvin Aquifer located in central Iran was developed using MODFLOW for spatial analysis of ASR before/after modernization. Besides, to investigate the operational performance of the water distribution systems in the status quo, a hydraulic flow simulation model of the surface water distribution systems, including the main open canal and lateral, was developed in MATLAB, calibrated, and verified by the observed operational data. Then, this hydraulic model was coupled with the developed automatic control systems, including the de-centralized & centralized real-time controllers, as the modernization alternatives. The hydraulic-operation simulation results reveal that the agricultural water distribution system's performance improved the reliability of the surface water delivery process by nearly 33% for the de-centralized control system and by approximately 35% for the centralized control system. Consequently, numerical modeling results indicate that the groundwater table will keep declining at an annual rate of about 1.5 m using the conventional operating system in the status quo. Also, the results show that groundwater extraction decreased by 45% and 60% in the de-centralized and centralized automated methods, respectively. Therefore, the proposed ASR approach in the present study, based on the operational automation of the surface flow within the irrigation district, can be introduced as a practical and reliable approach to upgrading the conjunctive surface-groundwater agricultural water distribution system in irrigation districts worldwide