The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help regulate emotions and stress levels.
This document provides information about the Technician Awards Certificate in Engineering 2565, including:
- An overview of the certificate, diploma, and advanced diploma levels of the program and guidance on guided learning hours.
- Details on internal and external candidate entry and assessment requirements.
- An outline of the assessments required for the Technician Certificate in Applied Mechanical Engineering, including two written exams and specified practical assignments.
- Component numbers and exam formats for assessing units in Engineering Fundamentals and Mechanical Technology.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help regulate emotions and stress levels.
This document provides information about the Technician Awards Certificate in Engineering 2565, including:
- An overview of the certificate, diploma, and advanced diploma levels of the program and guidance on guided learning hours.
- Details on internal and external candidate entry and assessment requirements.
- An outline of the assessments required for the Technician Certificate in Applied Mechanical Engineering, including two written exams and specified practical assignments.
- Component numbers and exam formats for assessing units in Engineering Fundamentals and Mechanical Technology.
The newsletter announces that the Council and Development Sub-Committee have been reviewing the Articles of Association and Bye-Laws to be presented at the upcoming AGM. It aims to reinforce development and expand the reach of the Society through affiliation and collaboration. Details are provided about the AGM, to be held on October 21st in London, including the program of presentations on engineering roles and city developments, and alternative dispute resolution.
The newsletter announces that the Council and Development Sub-Committee have been reviewing the Articles of Association and Bye-Laws to be presented at the upcoming AGM. It aims to reinforce development and expand the reach of the Society through affiliation and collaboration. Details are provided about the AGM, to be held on October 21st in London, including the program of presentations on engineering roles and city developments, and alternative dispute resolution.
Tom Johnson tjohnson@cices.org
ICES www.cices.org/scotland
ICE www.ice.org.uk/scotland
ICES South East
Chair: David Hutchings david.hutchings@jacobs.com
Secretary: David Bateman david.bateman@jacobs.com
ICES www.cices.org/south-east
ICE www.ice.org.uk/southeast
ICES South West
Chair: Paul Hutchings paul.hutchings@atkinsglobal.com
Secretary: David Bateman david.bateman@jacobs.com
ICES www.cices.org/south-west
The newsletter announces that the Council and Development Sub-Committee have been reviewing the Articles of Association and Bye-Laws to be presented at the upcoming AGM. It aims to reinforce development and expand the reach of the Society through affiliation and collaboration. Details are provided about the AGM, to be held on October 21st in London, including the program of presentations on engineering roles and city developments, and alternative dispute resolution.
The newsletter announces that the Council and Development Sub-Committee have been reviewing the Articles of Association and Bye-Laws to be presented at the upcoming AGM. It aims to reinforce development and expand the reach of the Society through affiliation and collaboration. Details are provided about the AGM, to be held on October 21st in London, including the program of presentations on engineering roles and city developments, and alternative dispute resolution.
Tom Johnson tjohnson@cices.org
ICES www.cices.org/scotland
ICE www.ice.org.uk/scotland
ICES South East
Chair: David Hutchings david.hutchings@jacobs.com
Secretary: David Bateman david.bateman@jacobs.com
ICES www.cices.org/south-east
ICE www.ice.org.uk/southeast
ICES South West
Chair: Paul Hutchings paul.hutchings@atkinsglobal.com
Secretary: David Bateman david.bateman@jacobs.com
ICES www.cices.org/south-west
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.