excavation ppt by nadir khattak
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The document summarizes excavation work done for construction of new wards at Lady Reading Hospital in Peshawar, Pakistan. It provides background on the hospital, describes the project details including cost, client, and consultants. It then discusses the excavation process used, called bulk pit excavation, and challenges faced with hard earth and small work area. Finally, it notes the equipment used for excavation and describes the soil layers found at the site.
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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.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
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Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
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IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
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3-6 June 2024, Niš, SerbiaDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
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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.
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Modelagem em função de transferencia. CSTR não-linear.
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Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
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This Presentation will give you a brief idea about what Computational Engineering at IIT Hyderabad has to offer.
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
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- 2. UNIVERSITY OF ENGINEERING AND TECHNOLOGY TAXILA DEPARTMENT OF CIVIL ENGINEERING Nadir murtaza Reg #16-CE-136 Section D
- 4. Construction of new wards in lady reading hospital Peshawar Introduction to LRH LRh is located at Peshawar in kpk of pakistan. It is the biggest hospital of kpk. It was established in 1924. It is located behind famous historical Qila balahisar.
- 6. Project information Cost:12 million Client: kpk Govt. Contractor: sarhad engineering and electric company pvt ltd. consultant: Allied engineering company. Engineer: Engineer Mohsin Zia Engineer Ahmad yar
- 7. Excavation: is the process of moving earth, rock or other materials with tools, equipment or explosives. Types of excavation: The types of excavation used in this project is Bulk pit excavation. Bulk pit Excavation: Primarily excavation of considerable length as well as of substantial volume or bulk that must be hauled from the site of operations.
- 13. Challenges in Excavation During the excavation of this project they face some problem which are. Hard earth surface Small area The surface of earth was to much tough and hard, so the machinery take more time than expected for excavation. Beacuase of the small area the machinery face difficulty while doing excavation process.
- 14. Equipment: The following are some equipment used in the excavation process of project. I. Excavator II. Dumper III. Tractor IV. shovel
- 16. Location of site: The site is located in LRH near a famous historical Qila Balahisar Peshawar kpk. Types of soil: There are two types of layers of earth was found there. The external surface of earth was hard and tough that’s way excavation takes more time than expected. While the internal surface of earth was of clay type.