Arduino Based Turkey Egg Incubator With Molen Rotation Method

Today's modern world of hatching many turkey eggs uses various incubators. Arduino-based turkey egg incubator with the molen rotation method uses an Arduino microcontroller that is connected to a DHT11 sensor for turkey egg incubator using the molen rotation method. Temperature and humidity are the main factors to determine the success at hatching of eggs, but also the need for the fertilization process in the eggs to be hatched because fertilization also determines the success rate at hatching eggs. Testing of the incubator is carried out directly from the turkey egg incubator at the temperature in the room and rotates it with the automatic spinning method with an angle of 360 ° every 4 hours. DHT11 can detect temperature and humidity in the incubator room, the optimal temperature for hatching turkey eggs is 37 ° -38 ° C and the optimal humidity is 55-60% RH, and the servo motor is able to move to move the egg rack according to the time specified. The measurement results of the DHT11 sensor readings are as desired with a minimum temperature reading of 37⁰C and a maximum temperature of 39⁰C with humidity that has been set at 55-60% and the molen rotation method runs according to the desired time every 6 hours for 4 times with 360 ⁰ rotation, at days 1-26 turkey eggs hatch with a result of 3: 2 in the sense that 3 successfully hatched and 2 failed to hatch.

A temperature reading of COVID-19 pandemic employee agility and resilience in South Africa

Orientation: Employee agility and resilience are central to the flourishing of employee and organisational life. The coronavirus disease 2019 (COVID-19) pandemic amplified stressors and added new challenges for employees in South Africa. The study reported here provides a temperature reading of the agility and resilience of South African employees in the context of the pandemic.Research purpose: The aim of this study was to engage in a temperature reading of South African employees’ agility and resilience during the COVID-19 pandemic.Motivation for the study: The study was motivated by the need to understand how South African employees fare in terms of their agility and resilience levels in the context of profound social and economic disruptive events such as the COVID-19 pandemic.Research approach/design and method: A cross-sectional survey design was used employing quantitative methodologies. A total of 185 permanently employed respondents from South Africa were conveniently sampled. Descriptive and inferential statistics were used to analyse the data.Main findings: Whilst respondents reported high resilience and agility capacity, the findings also suggest that respondents’ gender, age, upskilling intentions, size of employer, organisational communication and individual renewal strategies influence their resilience and agility behaviours.Practical/managerial implications: The study prompts a discussion on how practitioners can better serve the wellness agenda of organisational life during sustained periods of organisational stress.Contribution/value-add: This study extends the theoretical and practical debate on employee agility and resilience in South African context.

Design of a Start-Up Sequence Controller for a Mammography Machine

Mammography, which is also calledMastography, is the process of using low-energy X-rays to inspect the human breast for screening and diagnostics. The purpose of mammography is to detect breast cancer early, usually by looking for specific lumps or microcalcifications. The X-rays used are usually around 30 kVp. Excessive voltage to such a machine would be harmful to the patient. Proper monitoring of temperature and pressure needs to be ensured. To ensure this, a start-up sequence module is developed. The start-up sequence module reads the digitized voltage, pressure, and temperature reading from the sensor and asserts all the outputs to ensure that the machine is ready. The scan chain is formed of 13 scan flip-flops in this configuration. The synthesis mapped the design to 484 instances of cells in the open-source PDK technology. The design had a total area of 594 μm2, with a cell width of 0.297 μm, and a height of 0.99 μm.

IOT BASED HOUSEHOLD ELECTRICITY ENERGY MONITORING AND CONTROL

Internet of Things (loT) has opened up a myriad of applications in many areas, including medical and healthcare networks, smart home control, and environmental surveillance. IoT is supposed to bring about a large amount of progress in the ubiquitous computing sector. IoT-based energy management programs may allow a significant contribution to energy conservation. Therefore, this paper focuses on the design and implementation of an IoT based household electricity energy monitoring and electric bulb remote control for the reduction of electrical wastage using ESP 32-bit microcontroller. The ESP 32 microcontroller was used as the brain of the entire system which processes the energy consumption, temperature reading. Temperature monitoring can assist tremendously in the explosion and burning incidence avoidance, thereby saving lives and properties. The ESP32 microcontroller also handles the internet connectivity via its inbuilt WIFI module in order to transmit the real-time energy consumption, temperature reading, and electric bulb remote control over the internet. A MATLAB app was designed to serve as user interface for monitoring the household electricity energy consumption, temperature reading and electric bulb remote control via Thingspeak cloud server from MathWorks (makers of MATLAB) and also monitors the temperature and electricity consumed by the pressing iron and the hair dryer. Whenever, the electricity consumption or temperature reading exceeds the set threshold on the MATLAB app, a notification is sent to the user’s Email. The system could be used for reducing the wastage of electrical energy in the house by proper scheduling and monitoring of the appliances

Wrist and Forehead Temperature Measurement as Screening Methods During the COVID-19 Pandemic

Background: Temperature screening checkpoints have become widely distributed during the COVID-19 pandemic, using various contactless methods of temperature measurement, including wrist and forehead measurement. Aim: In this study we aim to investigate the sensitivity and specificity of these two temperature measurement methods – wrist and forehead – compared with the standards of sublingual or axillary measurement. We also aim to investigate the influence of age, gender, device brand and diurnal effect on the temperature reading. Methods: Participants were randomly assigned to one of two groups, each group using a different temperature measurement device. All participants had their forehead and wrist temperature measured, and this was compared to their axillary or sublingual readings. Results: The area under the curve for wrist measurement was 0.49 (95% CI 0.34 and 0.64), p>0.05, with a sensitivity of 46.2% and specificity of 53.3%, while the area under the curve for forehead measurement was 0.70 (95% CI 0.51, 0.89), p<0.05, with a sensitivity of 23.1% and specificity of 76.9%, PPV 1.59% and NPV 97.7%. Conclusion: Wrist and forehead temperature measurement is not accurate in detecting fever during the ongoing COVID-19 pandemic. Although forehead measurement is also not an ideal method, it nevertheless appears more consistent than wrist measurement.

OPTIMASI PEMBACAAN SUHU KAMERA TERMAL MENGGUNAKAN REGRESI LINIER

Fever is one of the symptoms of a person with Covid-19. Body temperature must be checked e before entering crowded areas such as schools, offices, shops, and hospitals. It is a mandatory protocol that must be done. One of the tools that can be used to check body temperature is a thermal camera. Thermal cameras have the disadvantage of a high temperature reading error. This is because the thermal camera used has a low resolution. This study aims to reduce the value of the temperature reading error on the thermal camera using the linear regression method. The linear regression method is able to reduce the error rate of temperature readings by 5.27% at 36 ° C reading. The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. Based on the results obtained, this study shows that linear regression can be applied to thermal cameras and provides a decrease in the error rate of temperature readings on thermal cameras

Programmable Logic Controller (PLC) Based Paint Viscosity Control System

Automatic control has been developed in various fields, one of which is paint quality control. Paint quality can be controlled from various categories, including paint quality based on its viscosity. Therefore, we need a system that can control the viscosity of the paint. The paint viscosity control system uses the PLC OMRON CP1E-NA20DRA with a heater as a heat source, and the LM35DZ sensor as a temperature reading sensor, and the RPM reading is used to calculate the viscosity value. The programming language used is the ladder diagram on the CX-Programmer. This system uses the PID (Proportional, Integral, and Derivative) Algorithm so that temperature control can be set at 30ºC so as not to affect the viscosity of the paint. In addition, this prototype provides two PID tuning options, namely manual and auto-tuning. Researchers get the results that a good temperature control system response has a PB value = 0.2%; Ti = 452.5s and TD = 66.6s. and control the accuracy level of paint viscosity control of 67.82%.

Study of Temperature Measurement Accuracy by Using Different Mounting Adhesives

Thermal compounds are adhesive used to improve heat conduction between two surfaces. It can be used to secure a thermocouple to a surface which the temperature is being measured. This paper studies the temperature accuracy when using different types of thermal adhesives to secure thermocouples to a metal surface. An aluminum block attached to heater resistors was heated up by supplying varying power levels to create different temperatures. The measured temperature is compared to a reference thermocouple in the aluminum block to check the accuracy of each thermocouple when it is secured with different adhesives. It was found using the Loctite 3873 to secure a thermocouple to a metal surface will produce the most accurate temperature reading with an error below 2.6°C. This enables researchers to use the appropriate adhesive to obtain the most accurate results and also to know what are the errors contributed by different adhesives.