Advanced operation system
•Download as PPTX, PDF•
0 likes•293 views
This document provides an introduction and overview of an Advanced Operating Systems course. The course will take approximately 5 weeks to complete and have 11 lessons. It will cover topics like abstractions, OS structure, virtualization, parallelism, distributed systems, and security. Each lesson will be released weekly and students are expected to spend around 6 hours per week to complete the material.
Report
Share
Report
Share
Recommended
OSI Model
The document describes the 6 layers of the OSI model for data transmission. It starts with user input being converted to data, then to a computer file, data segments, packets, frames, and finally bits for transmission. The last two sentences show an example transmission in binary format.
Ista presentation-dga
Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale (https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs169423)
Computer Networks Lab
This document summarizes experiments conducted on different network topologies using Cisco Packet Tracer. It describes experiments on bus, star, tree, ring, mesh and hybrid topologies. Each experiment lists the instruments used including computers, network devices and connection types. Diagrams and results are provided for each topology experiment.
008 20151221 Return of Frustrating Easy Domain Adaptation
The document proposes a simple and effective method called CORrelation ALignment (CORAL) for unsupervised domain adaptation. CORAL minimizes domain shift by aligning the second-order statistics of the source and target distributions without requiring any target labels. The method whitens the source distribution and recolors it with the target covariance matrix. Experiments on object recognition and sentiment analysis tasks show CORAL outperforms other unsupervised domain adaptation methods.
Canopy clustering algorithm
Canopy clustering is an unsupervised pre-clustering algorithm used to speed up K-means and hierarchical clustering on large datasets. It works by first selecting random points as canopy centers and assigning other points within a threshold distance to canopies. It then removes points within a smaller threshold to prevent them from being new centers, repeating until no points remain. This helps reduce the dataset size before the main clustering algorithm is applied.
A Multi-Agent System Approach to Load-Balancing and Resource Allocation for D...
In this research we use a decentralized computing approach to allocate and schedule tasks on a massively distributed grid. Using emergent properties of multi-agent systems, the algorithm dynamically creates and dissociates clusters
to serve the changing resource demands of a global task queue. The algorithm is compared to a standard First-in First-out (FIFO) scheduling algorithm. Experiments
done on a simulator show that the distributed resource allocation protocol (dRAP) algorithm outperforms the FIFO scheduling algorithm on time to empty
queue, average waiting time and CPU utilization. Such a decentralized computing approach holds promise for massively distributed processing scenarios like SETI@home and Google MapReduce.
Cyclometic Criticisms
Martin Shepperd critiques the cyclomatic complexity software metric in a 1988 article. He outlines the theoretical assumptions behind cyclomatic complexity and discusses modifications that have been suggested. Several controversies are raised about how cyclomatic complexity counts structures like else branches and case statements. The difficulty partly stems from applying the metric originally intended for Fortran to newer languages.
Magellan FOSS4G Talk, Boston 2017
Talk on Magellan, how does it compare to other big data tools, what is its performance like and whats next for the project
Recommended
OSI Model
The document describes the 6 layers of the OSI model for data transmission. It starts with user input being converted to data, then to a computer file, data segments, packets, frames, and finally bits for transmission. The last two sentences show an example transmission in binary format.
Ista presentation-dga
Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale (https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs169423)
Computer Networks Lab
This document summarizes experiments conducted on different network topologies using Cisco Packet Tracer. It describes experiments on bus, star, tree, ring, mesh and hybrid topologies. Each experiment lists the instruments used including computers, network devices and connection types. Diagrams and results are provided for each topology experiment.
008 20151221 Return of Frustrating Easy Domain Adaptation
The document proposes a simple and effective method called CORrelation ALignment (CORAL) for unsupervised domain adaptation. CORAL minimizes domain shift by aligning the second-order statistics of the source and target distributions without requiring any target labels. The method whitens the source distribution and recolors it with the target covariance matrix. Experiments on object recognition and sentiment analysis tasks show CORAL outperforms other unsupervised domain adaptation methods.
Canopy clustering algorithm
Canopy clustering is an unsupervised pre-clustering algorithm used to speed up K-means and hierarchical clustering on large datasets. It works by first selecting random points as canopy centers and assigning other points within a threshold distance to canopies. It then removes points within a smaller threshold to prevent them from being new centers, repeating until no points remain. This helps reduce the dataset size before the main clustering algorithm is applied.
A Multi-Agent System Approach to Load-Balancing and Resource Allocation for D...
In this research we use a decentralized computing approach to allocate and schedule tasks on a massively distributed grid. Using emergent properties of multi-agent systems, the algorithm dynamically creates and dissociates clusters
to serve the changing resource demands of a global task queue. The algorithm is compared to a standard First-in First-out (FIFO) scheduling algorithm. Experiments
done on a simulator show that the distributed resource allocation protocol (dRAP) algorithm outperforms the FIFO scheduling algorithm on time to empty
queue, average waiting time and CPU utilization. Such a decentralized computing approach holds promise for massively distributed processing scenarios like SETI@home and Google MapReduce.
Cyclometic Criticisms
Martin Shepperd critiques the cyclomatic complexity software metric in a 1988 article. He outlines the theoretical assumptions behind cyclomatic complexity and discusses modifications that have been suggested. Several controversies are raised about how cyclomatic complexity counts structures like else branches and case statements. The difficulty partly stems from applying the metric originally intended for Fortran to newer languages.
Magellan FOSS4G Talk, Boston 2017
Talk on Magellan, how does it compare to other big data tools, what is its performance like and whats next for the project
Computer Networks : CSC - 301 || BScCSIT
A basic Course Introduction of Computer Networks showing the question formats, Units to study, Credit Hours and Others.
It110 assignment-1 answer key
Question about computer organization _ Part 1
Peer TO Peer Computing
Units of CPU
The general representation of a system
The differentiate between standard and protoco
Converting
5th sem
This course covers computer networks and networking concepts. It discusses 3 main topics: networking techniques and the internet, networking protocol layers and models, and specific protocols like TCP, IP, and DNS. The goal is to introduce fundamental computer networking concepts and the layered networking model. Students will learn about networking principles, protocols, and applications through lectures and hands-on labs.
5th sem
This document provides information on a course titled "Computer Networks". The course is 3 credit hours and includes both theory and lab components. It introduces concepts of computer networking and discusses the different layers of the networking model. The course content covers topics such as types of networking techniques, the Internet, IP addressing, routing, transport layer protocols, and local area networks. The goal is to provide students an understanding of computer networking fundamentals.
2nd sem
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
2nd sem
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
SE-IT DSA THEORY SYLLABUS
The document outlines the program structure for the second year of engineering studies at the University of Mumbai for semesters 3 and 4. It includes the course codes, names, teaching schemes with credits, and examination schemes for the courses. The core courses cover topics like data structures, databases, algorithms, and computer programming. The document also provides course objectives and outcomes, as well as a detailed syllabus covering concepts like stacks, queues, linked lists, trees, graphs, searching, sorting, and applications of data structures. Assessment includes internal tests and an end semester exam.
How machines can take decisions
This document discusses how machines can make decisions using machine learning approaches. It provides an overview of machine learning vocabulary and techniques including supervised learning methods like regression and classification. It also discusses unsupervised learning and examples of clustering emails. The document then demonstrates simple linear and logistic regression models to predict outputs for given inputs. It discusses evaluating models through error measurement and mentions some other machine learning techniques. Finally, it provides an overview of neural networks including feedforward networks and different types like convolutional and recurrent neural networks.
How machines can take decisions
This document discusses how machines can make decisions using machine learning approaches. It provides an overview of machine learning vocabulary and techniques including supervised learning methods like regression and classification. It also discusses unsupervised learning and examples of clustering emails. The document then demonstrates simple linear and logistic regression models to predict outputs given inputs. It discusses evaluating models through error measurement and mentions several other machine learning techniques. Finally, it provides an overview of neural networks including feedforward networks and different types like convolutional and recurrent neural networks.
files_1570175665_204715750.pdf
This document outlines the teaching and evaluation scheme for the 3rd semester Information Technology program for the 2019-20 academic year. It includes:
- A list of 5 theory subjects and their credit hours, internal assessment marks, end semester exam marks, and total marks.
- A list of 4 practical subjects and their lab hours, internal assessment marks, and total marks.
- The total credit hours, internal assessment marks, end semester exam marks, and grand total marks for the semester.
- Minimum passing marks requirements and details on student centered activities.
- An outline of the curriculum for the 3rd semester Diploma in Information Technology program.
System integration final exam
This document contains a 50 question multiple choice exam on systems engineering concepts. The questions cover topics like the Vee model, system inputs/outputs, types of systems (open/closed, dynamic/static), system thinking, requirements analysis, life cycles, subsystems, interfaces, environments, and the roles of systems engineers. The majority of the questions have a single correct multiple choice answer related to foundational systems engineering principles and processes.
Kerala university m.sc. computer science syllabus
This document outlines the scheme and syllabus for the MSc Computer Science program offered by the Department of Computer Science at the University of Kerala.
The program is a 4 semester course with 3 semesters of taught courses and 1 semester of project work. The first two semesters cover core subjects like discrete structures, computer architecture, data structures, algorithms, operating systems, databases etc. along with electives. The third semester has more advanced subjects and electives. The fourth semester involves a project and viva voce.
The syllabus details are provided for the core subjects to be taught in the first semester, including topics like logic, graphs, automata theory for discrete structures, computer components, memory organization
Wait-free data structures on embedded multi-core systems
The document discusses wait-free data structures and task scheduling algorithms for embedded multi-core systems. It presents the objectives of evaluating existing approaches, implementing real-time compliant wait-free data structures, and defining benchmark scenarios. Specific data structures covered include pools, queues, and stacks. Pools are adapted using a compartment approach. The Kogan-Petrank queue is modified to remove its phase counter. Evaluation focuses on latency and buffering scenarios.
unit 1.pptx
This document provides details about a course on data structures taught at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. It includes information such as the course code, category, unit number, topic, and faculty name. It describes the course objectives as providing an introduction to basic concepts and techniques of linear and nonlinear data structures and analyzing various algorithms. It lists prerequisite and related courses, as well as intended course outcomes. It also includes a correlation of the course outcomes with program outcomes and lists recommended textbooks and online resources.
Srs
This document describes a routine management system project for a college. It was submitted by 5 students to fulfill the requirements for a Bachelor of Technology degree. The project involved developing a system to manage student and faculty timetables and schedules. It provides an overview of the system, outlines the activities for administrators, faculty and students. It also describes the software quality assurance plan, system analysis, requirements specification, architectural design, implementation, and maintenance of the system. The overall goal was to create a secure and flexible environment for managing academic records at the college.
CS403PC Operating System Lec 10 context switching.pptx
This document contains the syllabus and lecture notes for CS403PC: Operating System course. It provides an overview of the topics to be covered in Lecture 10, including process concepts and scheduling, context switching, and the information stored during context switches. It also lists the textbook and references for the course.
FAST MAP PROJECTION ON CUDA.ppt
This document discusses using CUDA on GPUs to accelerate map projection calculations. It presents a method for implementing the Universal Transverse Mercator projection on a GPU using CUDA. Experiments show the GPU implementation provides a 6-8x speedup over a CPU version when including data transfer times, and a 70-90x speedup when only considering calculation times. Two task assignment approaches are evaluated, with striped partitioning performing slightly better than a matrix distribution method. Future work is proposed to implement other GIS algorithms on GPUs to take advantage of the significant speed increases possible.
Operating System - Overview
The Operating System acts as a platform of information exchange between your computer's
hardware and the applications running on it. Most people are familiar with the Windows
Operating System family (like Windows 10, XP, or Vista) or Apple's suite of Operating Systems
(like Catalina, Mojave, or Sierra)
Information 2014_5_28-100
The document describes a new type of brain-like computer that operates without circuits, logic gates, or programmed software. It uses a multilayered architecture where smaller "computing seeds" self-assemble into larger seeds, forming a resonance chain from the smallest to largest seed. This frequency fractal enables wireless processing and distributed, simultaneous computation across all layers. The computer solves pattern search problems by matching input patterns to regions in its two giant, self-assembled columns of "if-then" arguments and phase transition rules. This non-algorithmic approach can provide instant decisions by exploring regions of the columns not defined by the system, relating it to Gödel's incompleteness theorem.
Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us
PWE: Datalog & ASP for the Rest of Us discusses using Possible Worlds Explorer (PWE) to make Datalog and Answer Set Programming (ASP) more accessible to non-experts. It covers topics like using provenance to explain query results, capturing rule firings to track provenance, representing provenance as a graph, using states to track derivation rounds, and declarative profiling of Datalog programs. The presentation advocates for tools like PWE that wrap Datalog/ASP engines to combine them with Python ecosystems and allow interactive use in Jupyter notebooks. This makes the languages more approachable and helps users build on existing work by experimenting further.
More Related Content
Similar to Advanced operation system
Computer Networks : CSC - 301 || BScCSIT
A basic Course Introduction of Computer Networks showing the question formats, Units to study, Credit Hours and Others.
It110 assignment-1 answer key
Question about computer organization _ Part 1
Peer TO Peer Computing
Units of CPU
The general representation of a system
The differentiate between standard and protoco
Converting
5th sem
This course covers computer networks and networking concepts. It discusses 3 main topics: networking techniques and the internet, networking protocol layers and models, and specific protocols like TCP, IP, and DNS. The goal is to introduce fundamental computer networking concepts and the layered networking model. Students will learn about networking principles, protocols, and applications through lectures and hands-on labs.
5th sem
This document provides information on a course titled "Computer Networks". The course is 3 credit hours and includes both theory and lab components. It introduces concepts of computer networking and discusses the different layers of the networking model. The course content covers topics such as types of networking techniques, the Internet, IP addressing, routing, transport layer protocols, and local area networks. The goal is to provide students an understanding of computer networking fundamentals.
2nd sem
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
2nd sem
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
SE-IT DSA THEORY SYLLABUS
The document outlines the program structure for the second year of engineering studies at the University of Mumbai for semesters 3 and 4. It includes the course codes, names, teaching schemes with credits, and examination schemes for the courses. The core courses cover topics like data structures, databases, algorithms, and computer programming. The document also provides course objectives and outcomes, as well as a detailed syllabus covering concepts like stacks, queues, linked lists, trees, graphs, searching, sorting, and applications of data structures. Assessment includes internal tests and an end semester exam.
How machines can take decisions
This document discusses how machines can make decisions using machine learning approaches. It provides an overview of machine learning vocabulary and techniques including supervised learning methods like regression and classification. It also discusses unsupervised learning and examples of clustering emails. The document then demonstrates simple linear and logistic regression models to predict outputs for given inputs. It discusses evaluating models through error measurement and mentions some other machine learning techniques. Finally, it provides an overview of neural networks including feedforward networks and different types like convolutional and recurrent neural networks.
How machines can take decisions
This document discusses how machines can make decisions using machine learning approaches. It provides an overview of machine learning vocabulary and techniques including supervised learning methods like regression and classification. It also discusses unsupervised learning and examples of clustering emails. The document then demonstrates simple linear and logistic regression models to predict outputs given inputs. It discusses evaluating models through error measurement and mentions several other machine learning techniques. Finally, it provides an overview of neural networks including feedforward networks and different types like convolutional and recurrent neural networks.
files_1570175665_204715750.pdf
This document outlines the teaching and evaluation scheme for the 3rd semester Information Technology program for the 2019-20 academic year. It includes:
- A list of 5 theory subjects and their credit hours, internal assessment marks, end semester exam marks, and total marks.
- A list of 4 practical subjects and their lab hours, internal assessment marks, and total marks.
- The total credit hours, internal assessment marks, end semester exam marks, and grand total marks for the semester.
- Minimum passing marks requirements and details on student centered activities.
- An outline of the curriculum for the 3rd semester Diploma in Information Technology program.
System integration final exam
This document contains a 50 question multiple choice exam on systems engineering concepts. The questions cover topics like the Vee model, system inputs/outputs, types of systems (open/closed, dynamic/static), system thinking, requirements analysis, life cycles, subsystems, interfaces, environments, and the roles of systems engineers. The majority of the questions have a single correct multiple choice answer related to foundational systems engineering principles and processes.
Kerala university m.sc. computer science syllabus
This document outlines the scheme and syllabus for the MSc Computer Science program offered by the Department of Computer Science at the University of Kerala.
The program is a 4 semester course with 3 semesters of taught courses and 1 semester of project work. The first two semesters cover core subjects like discrete structures, computer architecture, data structures, algorithms, operating systems, databases etc. along with electives. The third semester has more advanced subjects and electives. The fourth semester involves a project and viva voce.
The syllabus details are provided for the core subjects to be taught in the first semester, including topics like logic, graphs, automata theory for discrete structures, computer components, memory organization
Wait-free data structures on embedded multi-core systems
The document discusses wait-free data structures and task scheduling algorithms for embedded multi-core systems. It presents the objectives of evaluating existing approaches, implementing real-time compliant wait-free data structures, and defining benchmark scenarios. Specific data structures covered include pools, queues, and stacks. Pools are adapted using a compartment approach. The Kogan-Petrank queue is modified to remove its phase counter. Evaluation focuses on latency and buffering scenarios.
unit 1.pptx
This document provides details about a course on data structures taught at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. It includes information such as the course code, category, unit number, topic, and faculty name. It describes the course objectives as providing an introduction to basic concepts and techniques of linear and nonlinear data structures and analyzing various algorithms. It lists prerequisite and related courses, as well as intended course outcomes. It also includes a correlation of the course outcomes with program outcomes and lists recommended textbooks and online resources.
Srs
This document describes a routine management system project for a college. It was submitted by 5 students to fulfill the requirements for a Bachelor of Technology degree. The project involved developing a system to manage student and faculty timetables and schedules. It provides an overview of the system, outlines the activities for administrators, faculty and students. It also describes the software quality assurance plan, system analysis, requirements specification, architectural design, implementation, and maintenance of the system. The overall goal was to create a secure and flexible environment for managing academic records at the college.
CS403PC Operating System Lec 10 context switching.pptx
This document contains the syllabus and lecture notes for CS403PC: Operating System course. It provides an overview of the topics to be covered in Lecture 10, including process concepts and scheduling, context switching, and the information stored during context switches. It also lists the textbook and references for the course.
FAST MAP PROJECTION ON CUDA.ppt
This document discusses using CUDA on GPUs to accelerate map projection calculations. It presents a method for implementing the Universal Transverse Mercator projection on a GPU using CUDA. Experiments show the GPU implementation provides a 6-8x speedup over a CPU version when including data transfer times, and a 70-90x speedup when only considering calculation times. Two task assignment approaches are evaluated, with striped partitioning performing slightly better than a matrix distribution method. Future work is proposed to implement other GIS algorithms on GPUs to take advantage of the significant speed increases possible.
Operating System - Overview
The Operating System acts as a platform of information exchange between your computer's
hardware and the applications running on it. Most people are familiar with the Windows
Operating System family (like Windows 10, XP, or Vista) or Apple's suite of Operating Systems
(like Catalina, Mojave, or Sierra)
Information 2014_5_28-100
The document describes a new type of brain-like computer that operates without circuits, logic gates, or programmed software. It uses a multilayered architecture where smaller "computing seeds" self-assemble into larger seeds, forming a resonance chain from the smallest to largest seed. This frequency fractal enables wireless processing and distributed, simultaneous computation across all layers. The computer solves pattern search problems by matching input patterns to regions in its two giant, self-assembled columns of "if-then" arguments and phase transition rules. This non-algorithmic approach can provide instant decisions by exploring regions of the columns not defined by the system, relating it to Gödel's incompleteness theorem.
Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us
PWE: Datalog & ASP for the Rest of Us discusses using Possible Worlds Explorer (PWE) to make Datalog and Answer Set Programming (ASP) more accessible to non-experts. It covers topics like using provenance to explain query results, capturing rule firings to track provenance, representing provenance as a graph, using states to track derivation rounds, and declarative profiling of Datalog programs. The presentation advocates for tools like PWE that wrap Datalog/ASP engines to combine them with Python ecosystems and allow interactive use in Jupyter notebooks. This makes the languages more approachable and helps users build on existing work by experimenting further.
Similar to Advanced operation system (20)
Wait-free data structures on embedded multi-core systems
Wait-free data structures on embedded multi-core systems
CS403PC Operating System Lec 10 context switching.pptx
CS403PC Operating System Lec 10 context switching.pptx
Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us
Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us
More from Taewoo Kim
[김태우] Soscon 후기
This document summarizes sessions from the Samsung Open Source Conference from October 26-28. It discusses the Linux kernel boot process, IoT frameworks like IoT.js and JerryScript.js, and the Apache Horn project for big data and deep learning using a neuron-centric approach. The Linux kernel boot process initiates start_kernel() and mm_init() from over 15 million lines of code. IoT.js and JerryScript.js provide lighter alternatives to Node.js for IoT applications. Apache Horn is an open source project for deep learning that focuses on neurons.
Streaming join & lesson 4.
The document discusses a presentation on real-time analytics using Apache Storm. It covers basic Storm theory and setup, using Twitter streams with Storm, practices building streaming joins and exclamation topologies, and concludes with discussing student project teams analyzing sentiment, geography, ebola topics, and their use of tools like OpenCV.
[Taewoo Kim] Real-Time Analytics with Apache Storm
This document summarizes a study on real-time analytics using Apache Storm. It outlines four parts to the study: 1) learning the theory, setup, and basics of Storm, 2) using Storm with Twitter streams, 3) going beyond basic Storm concepts with an example join, and 4) participating in a Storm project and hackathon. It then describes two practices - parsing tweet URLs and tracking top hashtags - to demonstrate Storm's use for real-time analytics on Twitter data streams.
Real-Time Analytics with Apache Storm
This document outlines a plan to study real-time analytics using Apache Storm. It describes setting up Storm and completing basic tutorials on processing streaming data. The plan is to first learn Storm's theory and setup, then complete examples using Twitter streams and more advanced Storm techniques before participating in a Storm hackathon project.
Apache Storm by Skidmarkii
Storm is an open source distributed real-time computation system from Apache that allows processing streams of data in real-time. It is composed of spouts which act as sources of data streams and bolts which perform processing on the data. Topologies define the layout of spouts and bolts and how data flows between them. Common groupings in Storm include shuffle, fields, all, and global groupings which determine how data is distributed between processing tasks.
More from Taewoo Kim (16)
[Taewoo Kim] Real-Time Analytics with Apache Storm
[Taewoo Kim] Real-Time Analytics with Apache Storm
Recently uploaded
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
原版一模一样【微信：741003700 】【美国波士顿大学毕业证学历学位证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
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
Embedded 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.
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
For International shipping and maritime laws all wood must contain the ISPM 15 Stamp. Here is how and why.
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.
Casting-Defect-inSlab continuous casting.pdf
Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting
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.
The Python for beginners. This is an advance computer language.
Python language is very important language at this time. we can easily understand this language by these notes.
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
Bigdata of technology
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
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, SerbiaRecycled 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.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEM
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
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Computational Engineering IITH Presentation
This Presentation will give you a brief idea about what Computational Engineering at IIT Hyderabad has to offer.
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.
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.
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
原版一模一样【微信：741003700 】【(csu毕业证书)查尔斯特大学毕业证硕士学历】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
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
Recently uploaded (20)
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
The Python for beginners. This is an advance computer language.
The Python for beginners. This is an advance computer language.
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Recycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part III
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEM
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEM
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Advanced operation system
- 2. 강의 소개 Contents Index Lesson 1 – a : Abstraction 수강 계획 2
- 3. Course Summary Journey to understanding the role played by the Operating System Advanced Built-by Georgia Tech 6h/week, Approx. 5 weeks Join 2,288 Students Advanced Operating System : Abstractions and Virtualization Kishore Ramachandran, Charles Brubaker 3
- 4. Lesson 1 – a : Abstraction I don’t know how it work Number of Pins coming out of a chip AND logic gate Transistor INT data type Exact location of base pads in a baseball field 4
- 5. Lesson 1 – a : Abstraction From Google Earth to Electric holes OS, Compiler System Software Instruction Set ArchitectureISA Data Path + Control Machine organization True or False Seq & Comb Logic Element App Google Earth AND or ORLogic Gates White or BlackTransistor 5
- 6. Plan of Study One week, One lesson Lesson 1: Abstractions Lesson 2: OS Structure Lesson 3: Virtualization Lesson 4: Parallelism Lesson 5: Distributed Systems Lesson 6: Distributed Object Technology Lesson 7: Design and Implementation of Distributed Services Lesson 8: System Recovery Lesson 9: Internet Scale Computing L10: Real-Time and Multimedia L11: Security Lesson 6부터는 두 개의 강의를 수강 >> Total 8weeks 6