Slc restoring defaults
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To restore an SLC-500 processor to factory defaults: 1. Remove power and disconnect the battery from the processor. 2. For SLC-500 fixed I/O and models 5/01-5/02, short pins 14 and 28 on IC3 for 20 seconds using a paper clip or 10 ohm resistor. 3. For models 5/03-5/05, short the GND and VBB points for 60 seconds using a screwdriver after removing the CPU module and setting jumper J4 to protect. Restoring defaults will erase the ladder logic program and reset communications channels to default states.
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Modelagem de um CSTR com reação endotermica.pdf
Modelagem em função de transferencia. CSTR não-linear.
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
this notes have been created
by Eric36 at nyamata ttc
after readings
pe book for y2sme .
Recycled Concrete Aggregate in Construction Part III
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Iron and Steel Technology Roadmap - Towards more sustainable steelmaking.pdf
Iron and Steel Technology towards Sustainable Steelmaking
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
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Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
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Slides from talk presenting:
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
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, SerbiaEmbedded machine learning-based road conditions and driving behavior monitoring
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.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
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.
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
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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International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
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Bigdata of technology
ACEP Magazine edition 4th launched on 05.06.2024
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
DEEP 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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Slc restoring defaults
- 1. 14298 - Restoring Factory Defaults to SLC-500 Processors How can I restore a SLC-500 processor back to Factory Defaults? ( The Ladder Program will be lost if a processor is returned to Factory Defaults ) If the ladder program must be saved / recovered from the SLC Processor please see KnowBase Document 16846 Note: If a memory module, that has been configured for autoload is installed, after performing a reset. The old program will be restored into the processor RAM memory. SLC 500 Fixed I/O 1.Remove Power 2.Open CPU Compartment ( Series C units can not be factory reset ) 3.Disconnect Battery 4.Remove Memory Module ( 1747-M1 ) Skip step 4 if a Memory Module is not Installed 5.Locate RAM (IC3) 6.Connect Pins 14 and 28 (PWR & GND) with paper clip. See Diagram on the following page ( NOTE: The preferred connection method is to use a 10 Ohm Resistor ) Short for 20 Seconds or More
- 2. SLC 500 ( 5/01 & 5/02 ) 1.Remove Power 2.Remove CPU Module 3.Remove Memory Module ( EEPROM )- 1747-M1 ( Skip step 3 if a Memory Module is not Installed ) 4.Disconnect Battery 5.Locate RAM (IC3) 6.Connect Pins 14 and 28 (PWR & GND) with paper clip. ( NOTE: The preferred connection method is to use a 10 Ohm Resistor ) Short for 20 Seconds or More SLC 500 ( 5/03, 5/04 & 5/05 ) IMPORTANT: Jumper J4 on the processor must be set to the PROTECT position. (NOTE: Jumper J4 is used to Protect the Processor Firmware, and is not related to the Ladder Application) 1. Remove Power 2. Remove CPU Module
- 3. 3. Remove Memory Module ( 1747-M11 ) Skip step 3 if a Memory Module is not Installed 4. Disconnect Battery 5. Locate the GND & VBB points on the back side of the processor module. 6. Using a small flat blade screw driver short the GND & VBB points for 60 Seconds. (Take care to make a good metal-to-metal connection) IMPORTANT: Once Factory Defaults have been restored the ladder logic program will be lost and all communications channels will be reset to their default state, See Below: SLC-5/04 CH1 - DH+ ( 57.6k baud ) SLC-5/03 CH1 - DH485 ( 19.2k baud ) SLC-5/05 CH0 - DF1 Full Duplex 19.2k Baud, N, 8, 1, CRC SLC-5/04 CH0 - DF1 Full Duplex 1200 Baud, N, 8, 1, CRC SLC-5/03 CH0 - DF1 Full Duplex 1200 Baud, N, 8, 1, CRC Note: SLC 5/03 OS302 FRN 11 , SLC 5/04 OS401 FRN 8 or greater Channel 0 Defaults to 19.2KBaud Reference(s): 16846- Lost or Forgotten passwords procedure for the Micrologix, SLC-500, PLC-5 Family of controllers and RSLogix software. Processor is prompting for a password and password is either lost or forgotten.