BIL406-Chapter-1-Introduction.ppt
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This document provides an introduction to parallel computers. It discusses how parallel computers can be classified based on their machine structure and how parallel operations can be grouped by abstraction level or argument type. Parallel programming is necessary for tasks like modeling complex systems in various scientific domains like physics, biology, and weather. It also discusses concepts like speedup, efficiency, and different types of parallel computers and processing methods. Figures and tables are included to illustrate concepts like the von Neumann model versus the human brain in processing information.
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Kinematics 11th jpp- 01. ( Solved ) unacademy namo kaul on 14th may...
Literature Review Basics and Understanding Reference Management.pptx
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Modelagem de um CSTR com reação endotermica.pdf
Modelagem em função de transferencia. CSTR não-linear.
22CYT12-Unit-V-E Waste and its Management.ppt
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
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.
Understanding Inductive Bias in Machine Learning
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.
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
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%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
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.
Advanced control scheme of doubly fed induction generator for wind turbine us...
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
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6th International Conference on Machine Learning & Applications (CMLA 2024)
6th International Conference on Machine Learning & Applications (CMLA 2024)
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
Literature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
BIL406-Chapter-1-Introduction.ppt
- 1. Chapter 1 Introduction to Parallel Computers
- 2. Chapter 1 Introduction • 1.1 Fundamentals • 1.2 Speedup and Efficiency • 1.3 Parallel Computers
- 3. 1.1 Fundamentals • Parallel Computers can be classified according to their machine structure. • Parallel operations may be grouped by their abstraction level or by the types of argument. – 1. Sequential programs is special case of parallel programming.
- 4. – 2. Petri nets is useful tool for definition asynchronous parallelism. – 3. Petri nets and other (flow diagrams are used to discover data dependencies before designing an parallel program. – 4. The most common parallel programming languages and connection structures in a parallel computer system are fundamental for understanding parallel computations. • The growth of a plant is simultaneously influenced by number of factors. • The world is parallel; Natural systems , complex technical processes and even societal chances are highly parallel processes.
- 5. – 1. Quantum chemistry, stoical mechanics, relativistic physics. – 2. Cosmology and astrophysics. – 3. Computational fluid dynamics and turbulence. – 4. Material design an super conductivity. – 5. Biology, genome sequencing, genetic engineering, protein folding, enzyme activity, and cell modeling. – 6. Medicine and modeling human organs and bones. – 7. Global weather and environmental modeling.
- 6. – 8. Photo-realistic computer graphics Geological time), pattern and etc. recognition, (Parallel and Distributed Computing is necessary). • For example; (1994) a single iteration of ocean circulation takes 10 minutes and 30 billion floating point calculation. (50 million 3-D cell). • Molecular dynamics of a protein and surrounding water would take 31,688 years on Cray X/MP. • Parallel computers, Supercomputers, • Parallel processing, Multi-threading, Throughput, Pipelined (segments and stages) computations.
- 7. Figure 1 • Speed-up and efficiency. 1.2 Speedup and Efficiency
- 8. • However, many parallel super computer are developed. • Simple personal computer may carry out may operation simultaneously, multiple I/O via DMA and simple CPU has many parallel functional units Coprocessors. • Even arithmetic operation can be divided into parallel operations • Figure 1.1 Explains Von Neumann and Human Brain (Page 3) • Table 1.2 Illustrates incongruity of Von Neumann computer. 1.3 Parallel Computers
- 11. – Parallel computing is natural form of information processing. – Sequential Von Neumann computing successful but it is an artificial restriction. – Parallel representation of a problem has more information from the problem itself. Sequential can easily be constructed. – The goal of a parallel programming understandable programs and fast execution times.