Image Processing Test Bench for Robot Vision Using C#

Purpose: Nowadays, image processing is a well-known technological term. In some of the industries, it has practical needs. It is an essential tool for the process and robotic industry. Various popular frameworks and libraries are available to process the image. The OpenCV is one of the best and popular libraries for image processing. It was originally written in C++ by Intel. Now various wrappers are available to implement into the different programming languages. The OpenCvSharp is the wrapper of OpenCV. Those who are familiar with C# can use it. The new researcher who wants to integrate image processing into their project takes some time for setup, function writing, and integration. Here we created a test bench application for Image processing demonstration. It has been made with some usual function to process the image. It was created using visual studio 2022 and OpenCvSharp wrapper in C# language. The researcher can learn about various image processing algorithms without writing any code or giving little bits of effort. The complete project is available on GitHub. Anyone can download, experiment, and integrate into their project without any issue. Design/Methodology/Approach: We created a GUI (Graphical User Interface) based C# application. Using Nuget Package manager, installed two OpenCV wrapper packages. To invoke several functions, we add some buttons, and for changing the method’s parameter, we integrate some text boxes. We created some abstraction layers Between the OpenCvSharp wrapper and GUI. We made our custom module as portable as possible so that our researchers could easily incorporate it into their project. Findings/result: This unique image processing test bench is designed for new researchers trying to integrate image processing capability into their research work. It can take still images or moving images through the connected webcam, automatically sending the various commands and promptly observing the result. Originality/Value: This test bench has been arranged uniquely for the researcher. It might have some value to their research work. The unique feature like automatic trigger can help them send the series of commands without repeatedly typing or pressing the button to see the result. Paper Type: Experiment-based Research

A VOEvent-based automatic trigger system for the Murchison Widefield Array

The Murchison Widefield Array (MWA) is an electronically steered low-frequency (<300 MHz) radio interferometer, with a ‘slew’ time less than 8 s. Low-frequency (∼100 MHz) radio telescopes are ideally suited for rapid response follow-up of transients due to their large field of view, the inverted spectrum of coherent emission, and the fact that the dispersion delay between a 1 GHz and 100 MHz pulse is on the order of 1–10 min for dispersion measures of 100–2000 pc/cm3. The MWA has previously been used to provide fast follow-up for transient events including gamma-ray bursts (GRBs), fast radio bursts (FRBs), and gravitational waves, using systems that respond to gamma-ray coordinates network packet-based notifications. We describe a system for automatically triggering MWA observations of such events, based on Virtual Observatory Event standard triggers, which is more flexible, capable, and accurate than previous systems. The system can respond to external multi-messenger triggers, which makes it well-suited to searching for prompt coherent radio emission from GRBs, the study of FRBs and gravitational waves, single pulse studies of pulsars, and rapid follow-up of high-energy superflares from flare stars. The new triggering system has the capability to trigger observations in both the regular correlator mode (limited to ≥0.5 s integrations) and using the Voltage Capture System (VCS, 0.1 ms integration) of the MWA and represents a new mode of operation for the MWA. The upgraded standard correlator triggering capability has been in use since MWA observing semester 2018B (July–Dec 2018), and the VCS and buffered mode triggers will become available for observing in a future semester.

Predicting Automatic Trigger Speed for Vehicle-Activated Signs

Vehicle-activated signs (VAS) are speed-warning signs activated by radar when the driver speed exceeds a pre-set threshold, i.e. the trigger speed. The trigger speed is often set relative to the speed limit and is displayed for all types of vehicles. It is our opinion that having a static setting for the trigger speed may be inappropriate, given that traffic and road conditions are dynamic in nature. Further, different vehicle classes (mainly cars and trucks) behave differently, so a uniform trigger speed of such signs may be inappropriate to warn different types of vehicles. The current study aims to investigate an automatic VAS, i.e. one that could warn vehicle users with an appropriate trigger speed by taking into account vehicle types and road conditions. We therefore investigated different vehicle classes, their speeds, and the time of day to be able to conclude whether different trigger speeds of VAS are essential or not. The current study is entirely data driven; data are initially presented to a self-organising map (SOM) to be able to partition the data into different clusters, i.e. vehicle classes. Speed, time of day, and length of vehicle were supplied as inputs to the SOM. Further, the 85th percentile speed for the next hour is predicted using appropriate prediction models. Adaptive neuro-fuzzy inference systems and random forest (RF) were chosen for speed prediction; the mean speed, traffic flow, and standard deviation of vehicle speeds were supplied as inputs for the prediction models. The results achieved in this work show that RF is a reliable model in terms of accuracy and efficiency, and can be used in finding appropriate trigger speeds for an automatic VAS.

Is a modified Global Trigger Tool method using automatic trigger identification valid when measuring adverse events?

Objectives To evaluate a modified Global Trigger Tool (GTT) method with manual review of automatic triggered records to measure adverse events. Design A cross-sectional study was performed using the original GTT method as gold standard compared to a modified GTT method. Setting Medium size hospital trust in Northern Norway. Participants One thousand two hundred thirty-three records selected between March and December 2013. Main outcome measure Records with triggers, adverse events and number of adverse events identified. Recall (sensitivity), precision (positive predictive value), specificity and Cohen’s kappa with 95 % confidence interval were calculated. Results Both methods identified 35 adverse events per 1000 patient days. The modified GTT method with manual review of 658 automatic triggered records identified adverse events (n = 214) in 189 records and the original GTT method identified adverse events (n = 216) in 186 records. One hundred and ten identical records were identified with adverse events by both methods. Recall, precision, specificity and reliability for records identified with adverse events were respectively 0.59, 0.58, 0.92 and 0.51 for the modified GTT method. The total manual review time in the modified GTT method was 23 h while the manual review time using the original GTT method was 411 h. Conclusions The modified GTT method is as good as the original GTT method that complies with the GTTs aim monitoring the rate of adverse events. Resources saved by using the modified GTT method enable for increasing the sample size. The automatic trigger identification system may be developed to assess triggers in real-time to mitigate risk of adverse events.

We all know what we mean by treatment-resistant depression – don't we?

SummaryAlthough in common use, treatment-resistant depression is unhelpful both conceptually and practically. In this issue a new term, multiple-therapy-resistant major depressive disorder, is proposed; although it may be useful in guiding treatment options for patients with persisting depression, it should not be an automatic trigger for further, more invasive treatments.Declaration of interestsI.M.A. has been a consultant for pharmaceutical companies developing and marketing antidepressants and has been an author on publications that have used the term treatment-resistant depression.

Risk Assessment of Air Cannons at Sporting Events

This study looked to determine the safety of air cannons used at public events based on experimentally collected ballistic data. Specifically, the probable injuries to bystanders resulting from being hit by various projectiles launched from air cannons were investigated. Due to the rapid deceleration of projectiles fired from air cannons as they travel through the air, this study focuses on the worst case scenario: point blank impacts. Based on data collected using a chronograph and force plate, this study asserts that it is likely an air cannon operating under the conditions of this experiment can cause significant ocular, maxillofacial, laryngeal, and extremity injuries. To mitigate the risks posed by using air cannons, this study recommends the use of safety glasses for operators, mandatory operator training, automatic trigger locking mechanisms, frequent inspections of the cannon, regulations on the projectiles that can be fired, and the establishment of a minimum firing distance between the operator and bystanders.