The document discusses co-simulation interfaces for connecting distributed real-time simulators. It describes an ongoing project using an OPAL-RT and RTDS co-simulation interface with an FPGA board to connect the two simulators digitally in real-time. It also discusses using the VILLAS framework to enable geographically distributed real-time simulation across multiple labs separated by large distances. The framework uses VPN technology to securely connect simulators like OPAL-RT and RTDS at different university research centers for collaborative simulation.
The document discusses the State-Space Nodal (SSN) solver and its applications in real-time power system simulation. SSN allows large power systems to be simulated in real-time by reducing the number of network nodes through grouping, enabling parallelization. SSN has been used successfully for distribution grids, more electric aircraft, and super-large fusion reactor converter simulations. New developments include iterative methods for modeling switches and surge arresters in real-time.
FPGAs as Components in Heterogeneous HPC Systems (paraFPGA 2015 keynote) Wim Vanderbauwhede
This document provides a historical overview of the evolution of FPGA technology and programming approaches over several decades. It discusses early theoretical foundations in the 1930s-40s and the development of integrated circuits, hardware description languages, and high-level synthesis tools from the 1950s onwards. More recently, it describes the rise of heterogeneous computing using GPUs, FPGAs and other accelerators, and the ongoing challenges around programming such systems at a suitable level of abstraction.
This document contains a list of VLSI M.Tech and B.Tech project titles from 2014-2016. There are 66 project titles listed, ranging from 2012 to 2014. The titles are organized by year, with the project description or title provided. Contact information is also provided at the bottom for those interested in the projects.
Final Year Students Project
Opposite to Sripuram Bus Stop
Back of Rajadeepan Jewellers
Tirunelveli.
Phone:+91 - 8903410319
Mail: finalyearstudentsprojecttvl@gmail.com
web:www.finalyearstudentsproject.in
R2A20114A Circuit Simulation Using Ltspice And Using Timescale methodTsuyoshi Horigome
This document discusses using LTspice for circuit simulation and the timescale method. It was created by Bee Technologies and focuses on using LTspice and the timescale method for circuit simulation. The document provides information on simulating circuits using LTspice software and analyzing the results using the timescale modeling approach.
CabaLab is a USB device and software that replaces traditional scope and function generator equipment used in technical colleges and high schools. It offers the same classic features of a scope and FFT spectrum analyzer at a lower price point. The software also enables new education-oriented features like studying the frequency response of electrical devices and decoding infrared signals from remote controlled cars. It has been adopted by several schools and received an innovation award.
The document discusses the State-Space Nodal (SSN) solver and its applications in real-time power system simulation. SSN allows large power systems to be simulated in real-time by reducing the number of network nodes through grouping, enabling parallelization. SSN has been used successfully for distribution grids, more electric aircraft, and super-large fusion reactor converter simulations. New developments include iterative methods for modeling switches and surge arresters in real-time.
FPGAs as Components in Heterogeneous HPC Systems (paraFPGA 2015 keynote) Wim Vanderbauwhede
This document provides a historical overview of the evolution of FPGA technology and programming approaches over several decades. It discusses early theoretical foundations in the 1930s-40s and the development of integrated circuits, hardware description languages, and high-level synthesis tools from the 1950s onwards. More recently, it describes the rise of heterogeneous computing using GPUs, FPGAs and other accelerators, and the ongoing challenges around programming such systems at a suitable level of abstraction.
This document contains a list of VLSI M.Tech and B.Tech project titles from 2014-2016. There are 66 project titles listed, ranging from 2012 to 2014. The titles are organized by year, with the project description or title provided. Contact information is also provided at the bottom for those interested in the projects.
Final Year Students Project
Opposite to Sripuram Bus Stop
Back of Rajadeepan Jewellers
Tirunelveli.
Phone:+91 - 8903410319
Mail: finalyearstudentsprojecttvl@gmail.com
web:www.finalyearstudentsproject.in
R2A20114A Circuit Simulation Using Ltspice And Using Timescale methodTsuyoshi Horigome
This document discusses using LTspice for circuit simulation and the timescale method. It was created by Bee Technologies and focuses on using LTspice and the timescale method for circuit simulation. The document provides information on simulating circuits using LTspice software and analyzing the results using the timescale modeling approach.
CabaLab is a USB device and software that replaces traditional scope and function generator equipment used in technical colleges and high schools. It offers the same classic features of a scope and FFT spectrum analyzer at a lower price point. The software also enables new education-oriented features like studying the frequency response of electrical devices and decoding infrared signals from remote controlled cars. It has been adopted by several schools and received an innovation award.
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Marija Stevic during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Prof. Antonello Monti during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
VILLASframework - A toolset for local and geographically distributed real-tim...Steffen Vogel
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Steffen Vogel during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
Packet Optical SDN Field Trial for Multi-Layer Network OptimizationADVA
Jim Theodoras’ presentation, broadcast live from 2016 Internet2 Global Summit in Chicago, covered the work that ADVA Optical Networking and Juniper Networks have accomplished towards interoperability of SDN controllers and outlined the advantages of joint SDN management of router and transport resources.
RT15 Berkeley | ARTEMiS-SSN Features for Micro-grid / Renewable Energy Sourc...OPAL-RT TECHNOLOGIES
This document discusses using real-time simulation technologies to test phasor measurement units (PMUs) and PMU applications. It outlines different solvers for real-time simulation, including real-time phasor simulation and real-time electromagnetic transient simulation. It also discusses communication protocols supported by real-time simulators like IEC 61850 and IEEE C37.118. Examples are provided of how real-time simulation has been used to test PMUs and develop wide-area monitoring, protection, and control systems.
This document summarizes a research project on implementing smart grid technologies in the cities of Grenoble and Lyon, France. It includes 3 key points:
1. The project, called GreenLys, aims to help end users consume energy better, integrate local renewable production, handle peaks in production/consumption, and improve grid reliability. It involves 11 work packages including intelligent management solutions.
2. The electrical network was modeled using software like GAMS, MATLAB, and RT-Lab. Several scenarios were evaluated using the real-time simulator to analyze different loads, phases, and reactive power situations.
3. Future work includes integrating SCADA communication and sending real-time information between simulation tools and analog devices
SDN in GÉANT provides three key points:
1) GÉANT has implemented two generations of SDN testbeds to enable researchers to test novel network ideas.
2) The Network Service Interface (NSI) protocol solves the multi-domain SDN service challenge by enabling flexible, multi-domain service chaining across network domains.
3) Work is ongoing to integrate NSI into the SDN environment by adding OpenFlow constructs to the NSI topology descriptions to bridge intra-domain OpenFlow operations with inter-domain NSI provisioning.
IoT Meetup Budapest - The Open-CPS approachÁkos Horváth
The document discusses the OpenCPS project, which aims to develop methods and tools for multi-disciplinary simulation of cyber-physical systems through a model-driven approach. The project has 18 industrial and academic partners across 4 countries. It focuses on developing an FMI-based co-simulation environment, state machine debugging tools, and methods for efficient multi-core simulation. Key innovation areas include simulation of UML and Modelica models, real-time synchronization, and an FMI master simulation framework. An industrial use case involving simulation of an aircraft environmental control system is presented to demonstrate the project's techniques.
Software Defined Optical Networks - Mayur ChannegowdaCPqD
This document discusses software defined optical networks using SDN. Key points include:
- SDN and OpenFlow can decouple the data and control planes in optical networks for automated provisioning and unified control.
- There are challenges in applying SDN to optical networks including switching constraints, physical impairments, multi-domain/multi-technology operation, and network virtualization.
- OpenFlow extensions are needed to abstract optical network elements and account for characteristics like flexible grid networks, impairment awareness, and multi-dimensional resource allocation.
- Proof-of-concept demonstrations have shown the potential for media-aware SDN, packet and optical convergence, and virtualization across multiple domains.
Software Defined Optical Networks - Mayur ChannegowdaCPqD
This document discusses software defined optical networks using SDN. Key points include:
- SDN and OpenFlow can decouple the data and control planes in optical networks for automated provisioning and unified control.
- There are challenges in applying SDN to optical networks including switching constraints, physical impairments, multi-domain/multi-technology operation, and network virtualization.
- OpenFlow extensions are needed to abstract optical network elements and account for characteristics like flexible grid networks, impairment awareness, and multi-dimensional resource allocation.
- Proof-of-concept demonstrations have shown the potential for media-aware SDN, packet and optical convergence, and virtualization across multiple domains.
We build AI and HPC solutions. Expertise: highly optimized AI Engines and HPC Apps.
• HPC: accelerating time to results and adapting complex algorithms to GPU, FPGA, many-CPU architectures.
Leverage byteLAKE expertise in complex algorithms adaptation and optimization for NVIDIA GPUs, Xilinx Alveo FPGAs, Intel, AMD and ARM solutions. From single nodes to clusters.
More: www.byteLAKE.com/en/Alveo
VTT Technical Research Centre of Finland provides solutions to overcome major challenges in wireless access and communication systems, such as increasing capacity demands and energy consumption. They offer expertise in radio systems, hardware and software performance, smart antennas, and security. Their services include research, prototyping, testing, and commercialization of intellectual property to support technologies like 5G, LTE, WiFi and beyond.
Synchrophasor Applications Facilitating Interactions between Transmission and...Luigi Vanfretti
Distribution grid dynamics will become increasingly complex due to the transition from passive to active networks arising from the increase of renewable energy sources at medium and voltage level. A successful transition requires to increase the observability and awareness of the interactions between Transmission and Distribution (T&D) grids, particularly to guarantee adequate operational security.
This presentation explores how different technical means can facilitate interactions between TSOs and DSOs with the utilization of GPS-time-synchronized phasor measurements (aka Phasor Measurement Units (PMUs)) with millisecond resolution. If made available in actual T&D networks, such high-sampled data across operational boundaries allows an opportunity to extract information related to different time-scales.
As part of the work carried out in the EU-funded FP7 IDE4L project (http://ide4l.eu/), a specific use case, containing PMU-based monitoring functions, has been defined to support the architecture design of future distribution grid automation systems. As a result, the architecture can accommodate for key dynamic information extraction and exchange between DSO and TSO.
This presentation presents the use case and focuses on the technical aspects related to the development and implementation of the PMU-based monitoring functionalities that can provide means to facilitate technical co-operation between transmission and distribution operations.
Review Schneider Electric’s innovative and efficient upstream oil and gas offer and how to optimize remote assets. Benefit from industry expertise and live demonstrations that highlight reducing total cost of ownership and turning data into reliable information to drive business.
The document describes the Porto Living Lab project in Porto, Portugal which involves three sensing infrastructures: BusNet, HarbourNet, and UrbanSense. UrbanSense is an environmental sensor platform that collects data from over 500 sensors across the city to understand phenomena and their impacts. It involves sensor units that collect data and send it via various wireless networks to a cloud database. The sensors measure air quality, noise, weather and other environmental factors.
40 Powers of 10 - Simulating the Universe with the DiRAC HPC Facilityinside-BigData.com
In this deck from the Swiss HPC Conference, Mark Wilkinson presents: 40 Powers of 10 - Simulating the Universe with the DiRAC HPC Facility.
"DiRAC is the integrated supercomputing facility for theoretical modeling and HPC-based research in particle physics, and astrophysics, cosmology, and nuclear physics, all areas in which the UK is world-leading. DiRAC provides a variety of compute resources, matching machine architecture to the algorithm design and requirements of the research problems to be solved. As a single federated Facility, DiRAC allows more effective and efficient use of computing resources, supporting the delivery of the science programs across the STFC research communities. It provides a common training and consultation framework and, crucially, provides critical mass and a coordinating structure for both small- and large-scale cross-discipline science projects, the technical support needed to run and develop a distributed HPC service, and a pool of expertise to support knowledge transfer and industrial partnership projects. The on-going development and sharing of best-practice for the delivery of productive, national HPC services with DiRAC enables STFC researchers to produce world-leading science across the entire STFC science theory program."
Watch the video: https://wp.me/p3RLHQ-k94
Learn more: https://dirac.ac.uk/
and
http://hpcadvisorycouncil.com/events/2019/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this OFC presentation, Niall Robinson reviewed the current status of white box technology and explored the future of this exciting space. He also looked at the most recent activity of the Open Optical and Packet Transport Project, the design of the Voyager solution and at where this fast-moving networking industry initiative is headed.
The following presentation describes the use of numerical simulation to optimize the shape, elasticity and volume of the compensation chamber in an axial pump while minimizing pressure peaks.
This document lists 50 VLSI projects from 2016-2017 across various domains such as low power, high speed data transmission, area efficient/timing and delay reduction, audio/video processing, networking, verification, and Tanner/Microwind. The projects cover a range of topics including ECG acquisition systems, modular multiplication, adaptive radios, arrhythmia prediction, electrical capacitance tomography, approximate computing using memoization, FFT processors, error correction coding, carry skip adders, dynamic voltage and frequency scaling, code compression, turbo decoding, variable digital filters, parallel FFTs, MIMO communications, timing error correction, LU decomposition, FPGA logic architectures, LDPC decoding, minimum energy systems, elliptic curve multiplication, NB
The Impact of Advanced Optical Technologies on Transport SDNADVA
Achim Autenrieth presented this slide set at the Future Internet Assembly in March 2014. It's all about the impact of advanced optical technologies on transport SDN.
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Marija Stevic during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Prof. Antonello Monti during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
VILLASframework - A toolset for local and geographically distributed real-tim...Steffen Vogel
It is actively developed by the Institute for Automation of Complex Power Systems.
Presented by Steffen Vogel during ERIGrid - VILLAS workshop on 13th September 2018 at OFFIS, Oldenburg.
https://www.acs.eonerc.rwth-aachen.de
https://www.fein-aachen.org/projects/villas-framework/
Packet Optical SDN Field Trial for Multi-Layer Network OptimizationADVA
Jim Theodoras’ presentation, broadcast live from 2016 Internet2 Global Summit in Chicago, covered the work that ADVA Optical Networking and Juniper Networks have accomplished towards interoperability of SDN controllers and outlined the advantages of joint SDN management of router and transport resources.
RT15 Berkeley | ARTEMiS-SSN Features for Micro-grid / Renewable Energy Sourc...OPAL-RT TECHNOLOGIES
This document discusses using real-time simulation technologies to test phasor measurement units (PMUs) and PMU applications. It outlines different solvers for real-time simulation, including real-time phasor simulation and real-time electromagnetic transient simulation. It also discusses communication protocols supported by real-time simulators like IEC 61850 and IEEE C37.118. Examples are provided of how real-time simulation has been used to test PMUs and develop wide-area monitoring, protection, and control systems.
This document summarizes a research project on implementing smart grid technologies in the cities of Grenoble and Lyon, France. It includes 3 key points:
1. The project, called GreenLys, aims to help end users consume energy better, integrate local renewable production, handle peaks in production/consumption, and improve grid reliability. It involves 11 work packages including intelligent management solutions.
2. The electrical network was modeled using software like GAMS, MATLAB, and RT-Lab. Several scenarios were evaluated using the real-time simulator to analyze different loads, phases, and reactive power situations.
3. Future work includes integrating SCADA communication and sending real-time information between simulation tools and analog devices
SDN in GÉANT provides three key points:
1) GÉANT has implemented two generations of SDN testbeds to enable researchers to test novel network ideas.
2) The Network Service Interface (NSI) protocol solves the multi-domain SDN service challenge by enabling flexible, multi-domain service chaining across network domains.
3) Work is ongoing to integrate NSI into the SDN environment by adding OpenFlow constructs to the NSI topology descriptions to bridge intra-domain OpenFlow operations with inter-domain NSI provisioning.
IoT Meetup Budapest - The Open-CPS approachÁkos Horváth
The document discusses the OpenCPS project, which aims to develop methods and tools for multi-disciplinary simulation of cyber-physical systems through a model-driven approach. The project has 18 industrial and academic partners across 4 countries. It focuses on developing an FMI-based co-simulation environment, state machine debugging tools, and methods for efficient multi-core simulation. Key innovation areas include simulation of UML and Modelica models, real-time synchronization, and an FMI master simulation framework. An industrial use case involving simulation of an aircraft environmental control system is presented to demonstrate the project's techniques.
Software Defined Optical Networks - Mayur ChannegowdaCPqD
This document discusses software defined optical networks using SDN. Key points include:
- SDN and OpenFlow can decouple the data and control planes in optical networks for automated provisioning and unified control.
- There are challenges in applying SDN to optical networks including switching constraints, physical impairments, multi-domain/multi-technology operation, and network virtualization.
- OpenFlow extensions are needed to abstract optical network elements and account for characteristics like flexible grid networks, impairment awareness, and multi-dimensional resource allocation.
- Proof-of-concept demonstrations have shown the potential for media-aware SDN, packet and optical convergence, and virtualization across multiple domains.
Software Defined Optical Networks - Mayur ChannegowdaCPqD
This document discusses software defined optical networks using SDN. Key points include:
- SDN and OpenFlow can decouple the data and control planes in optical networks for automated provisioning and unified control.
- There are challenges in applying SDN to optical networks including switching constraints, physical impairments, multi-domain/multi-technology operation, and network virtualization.
- OpenFlow extensions are needed to abstract optical network elements and account for characteristics like flexible grid networks, impairment awareness, and multi-dimensional resource allocation.
- Proof-of-concept demonstrations have shown the potential for media-aware SDN, packet and optical convergence, and virtualization across multiple domains.
We build AI and HPC solutions. Expertise: highly optimized AI Engines and HPC Apps.
• HPC: accelerating time to results and adapting complex algorithms to GPU, FPGA, many-CPU architectures.
Leverage byteLAKE expertise in complex algorithms adaptation and optimization for NVIDIA GPUs, Xilinx Alveo FPGAs, Intel, AMD and ARM solutions. From single nodes to clusters.
More: www.byteLAKE.com/en/Alveo
VTT Technical Research Centre of Finland provides solutions to overcome major challenges in wireless access and communication systems, such as increasing capacity demands and energy consumption. They offer expertise in radio systems, hardware and software performance, smart antennas, and security. Their services include research, prototyping, testing, and commercialization of intellectual property to support technologies like 5G, LTE, WiFi and beyond.
Synchrophasor Applications Facilitating Interactions between Transmission and...Luigi Vanfretti
Distribution grid dynamics will become increasingly complex due to the transition from passive to active networks arising from the increase of renewable energy sources at medium and voltage level. A successful transition requires to increase the observability and awareness of the interactions between Transmission and Distribution (T&D) grids, particularly to guarantee adequate operational security.
This presentation explores how different technical means can facilitate interactions between TSOs and DSOs with the utilization of GPS-time-synchronized phasor measurements (aka Phasor Measurement Units (PMUs)) with millisecond resolution. If made available in actual T&D networks, such high-sampled data across operational boundaries allows an opportunity to extract information related to different time-scales.
As part of the work carried out in the EU-funded FP7 IDE4L project (http://ide4l.eu/), a specific use case, containing PMU-based monitoring functions, has been defined to support the architecture design of future distribution grid automation systems. As a result, the architecture can accommodate for key dynamic information extraction and exchange between DSO and TSO.
This presentation presents the use case and focuses on the technical aspects related to the development and implementation of the PMU-based monitoring functionalities that can provide means to facilitate technical co-operation between transmission and distribution operations.
Review Schneider Electric’s innovative and efficient upstream oil and gas offer and how to optimize remote assets. Benefit from industry expertise and live demonstrations that highlight reducing total cost of ownership and turning data into reliable information to drive business.
The document describes the Porto Living Lab project in Porto, Portugal which involves three sensing infrastructures: BusNet, HarbourNet, and UrbanSense. UrbanSense is an environmental sensor platform that collects data from over 500 sensors across the city to understand phenomena and their impacts. It involves sensor units that collect data and send it via various wireless networks to a cloud database. The sensors measure air quality, noise, weather and other environmental factors.
40 Powers of 10 - Simulating the Universe with the DiRAC HPC Facilityinside-BigData.com
In this deck from the Swiss HPC Conference, Mark Wilkinson presents: 40 Powers of 10 - Simulating the Universe with the DiRAC HPC Facility.
"DiRAC is the integrated supercomputing facility for theoretical modeling and HPC-based research in particle physics, and astrophysics, cosmology, and nuclear physics, all areas in which the UK is world-leading. DiRAC provides a variety of compute resources, matching machine architecture to the algorithm design and requirements of the research problems to be solved. As a single federated Facility, DiRAC allows more effective and efficient use of computing resources, supporting the delivery of the science programs across the STFC research communities. It provides a common training and consultation framework and, crucially, provides critical mass and a coordinating structure for both small- and large-scale cross-discipline science projects, the technical support needed to run and develop a distributed HPC service, and a pool of expertise to support knowledge transfer and industrial partnership projects. The on-going development and sharing of best-practice for the delivery of productive, national HPC services with DiRAC enables STFC researchers to produce world-leading science across the entire STFC science theory program."
Watch the video: https://wp.me/p3RLHQ-k94
Learn more: https://dirac.ac.uk/
and
http://hpcadvisorycouncil.com/events/2019/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this OFC presentation, Niall Robinson reviewed the current status of white box technology and explored the future of this exciting space. He also looked at the most recent activity of the Open Optical and Packet Transport Project, the design of the Voyager solution and at where this fast-moving networking industry initiative is headed.
The following presentation describes the use of numerical simulation to optimize the shape, elasticity and volume of the compensation chamber in an axial pump while minimizing pressure peaks.
This document lists 50 VLSI projects from 2016-2017 across various domains such as low power, high speed data transmission, area efficient/timing and delay reduction, audio/video processing, networking, verification, and Tanner/Microwind. The projects cover a range of topics including ECG acquisition systems, modular multiplication, adaptive radios, arrhythmia prediction, electrical capacitance tomography, approximate computing using memoization, FFT processors, error correction coding, carry skip adders, dynamic voltage and frequency scaling, code compression, turbo decoding, variable digital filters, parallel FFTs, MIMO communications, timing error correction, LU decomposition, FPGA logic architectures, LDPC decoding, minimum energy systems, elliptic curve multiplication, NB
The Impact of Advanced Optical Technologies on Transport SDNADVA
Achim Autenrieth presented this slide set at the Future Internet Assembly in March 2014. It's all about the impact of advanced optical technologies on transport SDN.
Similar to Co-simulation interfaces for connecting distributed real-time simulators (20)
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
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.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
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.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
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.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
2. Co-simulation interfaces for connecting distributed
real-time simulators | Steffen Vogel | 06.01.2016
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Agenda
■ EON Energy Research Center
≡ Institute for Automation of Complex Power Systems
■ OPAL - RTDS co-simulation Interface
≡ On-going work
■ Geographically-distributed simulation
≡ VILLAS
= VILLASnode / fpga
≡ ERIC LAB
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■ June 2006: the largest research co-operation in Europe between a private
company and a university was signed
■ Five new professorships in the field of energy technology were defined across 4
faculties
■ Research areas: energy savings, efficiency and sustainable power sources
The E.ON Energy Research Center
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ICT 4 EnergyGrid Operations
ACS Research Areas
§ Fundamentals of Grid Dynamics
§ Network Stability
§ Hybrid DC/AC Networks
§ Grid Monitoring
§ Grid Automation
§ Integration of Renewables
§ Energy as data-driven systems
§ Distributed Computing for Complex
System Simulation
§ Distributed Intelligence for Energy
Systems
§ Cloud applications for energy
§ Real-Time Systems
§ Smart Cities
§ Future Energy Networks
§ Center for Wind Drives
§ Future Internet
Applications
5. Co-simulation interfaces for connecting distributed
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Real Time Laboratory at ACS
ACS Real Time Laboratory
6. Co-simulation interfaces for connecting distributed
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Lab as a Network of Experiments
LTE for Substation
control & monitoring (Ericcson)
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OPAL – RTDS: Co-simulation Interface
■ Fully-digital coupling of two digital real-time simulators
≡ OPAL-RT Technologies: OP5600: eMegaSim or HyperSim
≡ RTDS Technologies: GPC / PB5 based racks
■ No ADCs, DACs
■ In-band synchronization
≡ 1 time-step latency between simulators
■ 64x 32 bit floats or integer values per direction and TS
≡ More values with multiplexing or multiple fibers
≡ Small-dt mode
■ Medium: Single fiber connection between
≡ Xilinx ML605 FPGA board: SFP fiber module
≡ GTIO peripheral port of RTDS GPC card
No Noise & Unlimited dynamic range
Less cabeling
10. Co-simulation interfaces for connecting distributed
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OPAL – RTDS: Setup
RTDS Rack next to OPAL-RT OP5600
RTDS rear panel: GPC cards
OP5600 rear panel: internal fiber connection to ML605 SFP port
RTDS racks
OPAL-RT
OP5600
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OPAL-RT – RTDS co-simulation interface
■ Problem
≡ RTDS is using a proprietary protocol
on it‘s fibers
≡ Synchronization
≡ Latency
≡ RTDS internal scheduling
= Control signals vs.
= Power System solution
■ Solution
≡ RTDS_InterfaceModule (aka. GTFPGA)
≡ Synthesized FPGA netlist provided by RTDS
≡ User-friendy access to proprietary interface
≡ OPAL-RT can be externally synchronized
by using ML605 FPGA IO‘s
≡ RTDS can be externally synchronized
by using GTSYNC extension module
≡ Using a dedicated master clock for both
≡ Transmission Line Interface (TLI)
= Same as of inter-rack communication
≡ CBuilder implementation of TLI & GTFPGA?
= Open question...
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OPAL – RTDS: RT-XSG model
Xilinx ML605
Greyzone
RT-XSG Model
Blackbox:
RTDS_InterfaceModule
SFP / Fiber
Synchronization
AIO/DIO
Mux
User
adaptable
External
Synchronization
User
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RTDS
GTFPGA
CPU
Bank
t0 t1
t'0
OPAL – RTDS: Timing
Computation
Update
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OPAL – RTDS: Timing 2
Computation
Update
RTDS
GTFPGA
CPU
Bank
t0 t1
t'0
RTDS
GTFPGA
CPU
Bank
t0 t1
t'0
(a) Serial (a) Parallel
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OPAL – RTDS: Results
■ 1 time-step latency between RTDS and OPAL-RT
≡ Fully deterministic: no jitter, noise or overruns
■ RT-LAB simulation is synchronized to RTDS simulation timestep (20 uS)
≡ Synchronization signal can be about 400 ns delayed
≡ Smaller-dt possible on FPGA
■ RT-XSG offers high degree of adaptability
≡ Multi-rate co-simulation
≡ Several scheduling schemes
■ RT-LAB simulation can wait for start of RSCAD simulation case
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Ongoing work
■ Generic PCIe-based interface to RTDS
≡ PCIe based co-simulation framework
≡ VILLAS integration
■ RT Co-simulation with 𝑁 > 2 simulators
■ Other clock sources for time-step synchronization
≡ OPAL as master
≡ Synchronizing RTDS with a GTSYNC card (PPS generated by ML605)
≡ GPS / PTP IEEE 1588
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External Links
Uni. South Carolina, US
Joint Research Center, EU
Politecnico di Turino, Italy
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Virtually Interconnected Laboratories for LArge systems Simulation
Laboratory
𝑵
…
Soft RT Integration Layer
Hard RT Integration Layer
Historical
DB
Data as a
Service
Data
Analytics
Cloud
platform
Visualisation
User
interaction
Simulation as
a Service
CWD PGSACS
VILLASnode VILLASnode VILLASnode
VILLASnode VILLASnode
VILLASnode
Offline Integration Layer
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Geographically distributed simulation
■ Co-simulation over large distances and unreliable connections
■ Why
≡ Share knowledge & protect IP
≡ „Simulation as a Service“
≡ Large-scale simulation of UCTE grid
■ Network infrastructure
≡ Research / university / metropolitan area networks (MAN)
≡ Non-deterministic latency
≡ No real-time guarantees at all
■ Coupling in dynamic phasor (DP) domain
≡ Latency insensitve
≡ Transmission Line Interfaces based on travelling wave models
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Pro Of Grids: ACS – SINTEF (Aug 2014)
■ First tests between ACS in Aachen and SINTEF in Trondheim
■ Facts
≡ Air-line distance: 1500 km
≡ One-way delay: around 20-30 mS
≡ Simulators: 2x OPAL-RT OP5600
■ Difficulties
≡ Red tape
= Security / Firewalls
= Software compatability
≡ Non-deterministic & high network delay
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First test: Topology
■ 1 VILLASnode per Lab
≡ Monitoring, Statistics
≡ Interface algorithms
≡ VPN for Encryption
≡ Local real-time co-simulation
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Tinc VPN: Principle & Topology
ACS
JRC Polito
FRA
Meta-connection
Direct Data-path
Firewall
Public node (FRA) supports
establishment of direct
connections between
otherwise firewall‘ed nodes
(ACS, JRC & Polito)
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Network link: ACS - SINTEF
■ Mostly university & research networks:
≡ RWTH, NTNU, DFN, Geant, NORDUnet, UNINETT
■ Delay caused by geographical distance & congested routers
■ VPN can be used to intentionally change routing
≡ Can minimize delay: 55 ms => 40 ms RTT
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VILLASnode
Goals Low & deterministic latency
■ Framework for geographically distributed co-simulation
■ Acts as a gateway between a variety of different node-types
■ Developed inhouse by ACS
■ Object oriented low-level C for best performance
■ Only depends on open source tools & libraries
■ Make use of Linux real-time features (PREEMPT_RT patchset)
■ Multi-threaded, lock-less design
■ Pins pathes, nodes & IRQs to reserved CPU cores
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VILLASnode: Overview
§ Router for sample / value based simulation data
≡ 1-to-n forwarding of sample values
≡ Concept of unidirectional paths and nodes
VILLASnode
Node: OPAL-RT
Node: LabVIEW
Node: RTDS
Node: Web
VILLASnode
Path1: OPAL -> RTDS + Web
Path2: RTDS -> OPAL + LabVIE
PathN: SimN -> ???Example:
Path2: LabVIEW-> VILLASnode
28. Co-simulation interfaces for connecting distributed
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VILLASnode: Overview
§ Router for sample / value based simulation data
≡ 1-to-n forwarding of sample values
≡ Concept of unidirectional paths and nodes
Path 1: OPAL -> RTDS + Web
Path 2: RTDS -> OPAL + LV
Path 2: LV -> VILLASnode
OPAL
Sim.
Lab
VIEW
VILLAS
node
Web-
Interf.
RTDS
Sim.
Path n: Node N -> Node M
VILLASnode
29. Co-simulation interfaces for connecting distributed
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ERIC Lab Demonstration (Oct 2015)
Ispra
(Italy)
Petten
(Netherland)
Consumer Behavior Model
Supervisor
GE Pub/Sub Context
Broker
GE Application
Mashup
Web
Browser
FIWARE
platform
UDP
UDP
Tinc VPN
(point-to-point)
NGSI
Read from file
Turin
(Italy)
Distribution System
Simulation
Aachen
(Germany)
Transmission System
Simulation
220 kV
22 kV22 kV 22 kV
63
MVA
55
MVA
63
MVA
Tinc VPN
(point-to-point)
UDP UDP
VILLASnode VILLASnode
VILLASnode
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Outlook: Combine Hard-RT Interface Layer with Soft-RT IL
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E.ON Energy Research Center
Mathieustraße 10
52074 Aachen
Germany
http://www.acs.eonerc.rwth-aachen.de
Prof. Antonello Monti
amonti@eonerc.rwth-aachen.de
Marija Stevic
mstevic@eonerc.rwth-aachen.de
Steffen Vogel
stvogel@eonerc.rwth-aachen.de
Contact
32. Co-simulation interfaces for connecting distributed
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References
[1] VILLAS project
http://www.acs.eonerc.rwth-aachen.de/cms/E-ON-ERC-ACS/Forschung/Projekte/~krkg/VILLAS-Virtually-Interconnected-Labora/
[2] Tinc VPN
http://www.tinc-vpn.org
[3] OPAL-RT Press Release: RTDS-OPALinterface
http://www.opal-rt.com/press-release/eon-energy-research-center-builds-first-interface-between-opal-rt-and-rtds-technologie
[4] ERIC Lab Website
http://www.eric-lab.eu/drupal/contact
[5] JRC Technical Report: A European Platform for Distributed Real Time Modelling &
Simulation of Emerging Electricity Systems
https://ec.europa.eu/jrc/en/publication/european-platform-distributed-real-time-modelling-simulation-emerging-electricity-systems
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Speaker: Steffen Vogel
■ In 2009, privacy concerns raised by the deployment of new smart-meters lead him
to start the open-source project „volkszaehler.org“ which offers everyman with
insights to their unique consumer behaviour.
■ His leisure time is packed with contributes to open-source projects and an
addiction to running.
■ After finishing his thesis, Steffen will be a future intern at OPAL-RT and looking for
employment starting from April 2017.
http://www.steffenvogel.de
■ Steffen Vogel is studying electrical engineering at RWTH
Aachen University.
■ He is currently writing his master thesis at the Institute
for Automation of Complex Power Systems in the area of
real-time co-simulation.
■ His main focus is on computer engineering with a special
interest in FPGA design.