The document discusses a 3D comic framework and converter for a university course. It includes details on content layout with tables, smartart for task groups, and slide titles for halls of justice and starship warp drive. Paradigms and logic are mentioned for the 3D world.
Semi supervised classification with graph convolutional networks哲东 郑
A graph convolutional network model is proposed for semi-supervised learning that takes into account both the graph structure and node features. The model uses a graph convolutional layer that approximates spectral graph convolutions using a localized first-order approximation. This allows the model to be applied to large-scale problems. The model is evaluated on several benchmark semi-supervised classification datasets where it achieves state-of-the-art performance.
The document summarizes computing the definite integral of y^2 from 0 to 2. It is evaluated numerically using left Riemann sums, assuming the interval [0,2] is divided into n equal subintervals. The left sum approximation approaches the exact value of 10/3 as n increases.
This document discusses the principles of radar and factors that affect multipath power return and backscattering clutter measurements. It explains that to calculate the factor affecting multipath power return, the path length difference between the direct path and specular reflection path must be determined. It also notes that the grazing angle is needed to calculate the normalized radar cross section of backscattering clutter. The document presents equations involving range, path lengths, angles, and distances in radar measurements.
This document discusses programming control structures. It lists several basic programming constructs including arithmetic expressions, variables, and looping statements like while, for, and do-while loops.
This document discusses programming control structures. It lists several common loop and conditional statements used in many programming languages including while, for, and do-while loops.
This document discusses programming control structures. It lists several basic programming constructs including arithmetic expressions, variables, and looping statements like while, for, and do-while loops.
The document discusses a 3D comic framework and converter for a university course. It includes details on content layout with tables, smartart for task groups, and slide titles for halls of justice and starship warp drive. Paradigms and logic are mentioned for the 3D world.
Semi supervised classification with graph convolutional networks哲东 郑
A graph convolutional network model is proposed for semi-supervised learning that takes into account both the graph structure and node features. The model uses a graph convolutional layer that approximates spectral graph convolutions using a localized first-order approximation. This allows the model to be applied to large-scale problems. The model is evaluated on several benchmark semi-supervised classification datasets where it achieves state-of-the-art performance.
The document summarizes computing the definite integral of y^2 from 0 to 2. It is evaluated numerically using left Riemann sums, assuming the interval [0,2] is divided into n equal subintervals. The left sum approximation approaches the exact value of 10/3 as n increases.
This document discusses the principles of radar and factors that affect multipath power return and backscattering clutter measurements. It explains that to calculate the factor affecting multipath power return, the path length difference between the direct path and specular reflection path must be determined. It also notes that the grazing angle is needed to calculate the normalized radar cross section of backscattering clutter. The document presents equations involving range, path lengths, angles, and distances in radar measurements.
This document discusses programming control structures. It lists several basic programming constructs including arithmetic expressions, variables, and looping statements like while, for, and do-while loops.
This document discusses programming control structures. It lists several common loop and conditional statements used in many programming languages including while, for, and do-while loops.
This document discusses programming control structures. It lists several basic programming constructs including arithmetic expressions, variables, and looping statements like while, for, and do-while loops.
Kineograph: Taking the Pulse of a Fast-Changing and Connected WorldQian Lin
Kineograph is a system for processing large-scale, time-sensitive graph data from continuous data streams. It uses an in-memory distributed graph storage and computation approach with three key aspects: 1) incremental graph mining on static snapshots to provide timeliness guarantees, 2) a graph partitioning scheme without locality considerations, 3) an epoch commit protocol using a progress table to ensure consistency during updates. It demonstrates the ability to incrementally compute graph algorithms like PageRank, shortest paths, and k-exposure on real-world Twitter graphs with millions of vertices and edges being updated at 100K per second.
1. The document discusses the design of a carry-ripple adder. It defines the generate, propagate, and kill functions used for each bit in the adder.
2. The carry for each bit is calculated by grouping the generate and propagate functions of lower order bits. The sum is calculated using the generate and propagate functions as well as the carry in.
3. The critical path in a carry-ripple adder goes through a chain of AND-OR gates rather than majority gates when using the grouped generate-propagate approach.
This document summarizes an approach for solving the train timetabling problem using a permutation-based evolutionary algorithm. It describes using a genetic algorithm with mutation operators that swap elements in the permutation representation. Constraints like minimum spacing between trains are handled by using a "kick" operator that removes conflicting trains from the schedule to resolve issues. Initial results on a large real-world problem showed the approach finding feasible solutions in 2/3 of cases and improving to always find solutions with more optimization.
This document contains a model examination for the subject Propulsion-II (Aeronautical Engineering) with questions in two parts - Part A and Part B.
Part A contains 10 multiple choice questions related to topics like impulse and reaction blades, turbine blade cooling, ramjet engine T-S diagram, components of pulse jet engine, applications of rocket propulsion, specific propellant consumption, types of propellant injectors, properties of liquid propellant, and thrust coefficient and nuclear propulsion.
Part B contains 5 long answer questions related to topics like lexical analyzer, transition diagrams, regular expressions, non-deterministic finite automata, deterministic finite automata, grammar, parsing tables, translation schemes, three address code, symbol
This document lists Matlab projects in three main categories: major Matlab features, domains for Matlab projects, and advanced modules for Matlab projects. Some of the key features and capabilities of Matlab mentioned include functions and data plotting, interfacing with other languages, user interface creation, and matrix manipulations. Notable domains listed for Matlab projects are embedded systems, surveillance/security, biomedical imaging, image processing, and neural networks/remote sensing. Specific advanced project modules listed include real-time fire detection, image hiding/cryptography, visual object tracking, and energy conservation using color coding.
https://github.com/leobenkel/Zparkio
Slides presented during the ScalaSF meetup on Thursday, March 26, 2020.
https://www.meetup.com/SF-Scala/events/268998404/
ZparkIO was on version 0.7.0 at the time, so things might be out of date.
Tailoring Redis Modules For Your Users’ NeedsRedis Labs
This document discusses using Redis modules to tailor Redis for users' needs. Redis modules allow adding new commands, data types, and APIs to Redis in order to make Redis understand custom data, speak custom languages, and do custom work. With modules, code can be consolidated across platforms, network hops minimized, and computation moved closer to data. The ReDe module is provided as an example of implementing an event dehydration algorithm in Redis using a module.
Since its first 1.12 release on July 2016, Docker Swarm Mode has matured enough as a clustering and scheduling tool for IT administrators and developers who can easily establish and manage a cluster of Docker nodes as a single virtual system. Swarm mode integrates the orchestration capabilities of Docker Swarm into Docker Engine itself and help administrators and developers with the ability to add or subtract container iterations as computing demands change. With sophisticated but easy to implement features like built-in Service Discovery, Routing Mesh, Secrets, declarative service model, scaling of the services, desired state reconciliation, scheduling, filters, multi-host networking model, Load-Balancing, rolling updates etc. Docker 17.06 is all set for production-ready product today. Join me webinar organised by Docker Izmir, to get familiar with the current Swarm Mode capabilities & functionalities across the heterogeneous environments.
MATLAB is a numerical computing environment and programming language developed in the 1970s. It was originally designed for matrix computations but has grown to include tools for data analysis, visualization, and GUI design. MATLAB allows both numeric calculations and programming and is commonly used in engineering, science, and mathematics applications. It includes toolboxes for tasks like signal processing, control systems, and computer vision.
This document discusses Matlab-based major projects for electrical and computer engineering (ECE). It lists the major domains supported for ECE projects as microelectronics, control systems, electrical energy and power systems, microwave and communication systems, and sensing, imaging and signal processing. It also describes hardware techniques like code generation, FPGA programming, and interfacing Matlab with other software. Finally, it provides examples of major ECE applications developed using Matlab like wireless motor control systems and solar tracking systems.
MBrace is a programming model and cluster infrastructure for large-scale distributed computing inspired by F# asynchronous workflows. It provides a declarative way to compose cloud computations using a monadic programming model. It runs on .NET and provides fault tolerance, elasticity, and multitasking capabilities. Performance tests on Azure showed MBrace can perform comparably to Hadoop for algorithms like distributed grep and k-means clustering.
This is a set of modified MacRuby presentation slides given at the Pittsburgh Ruby Brigade meeting on Nov 5, 2009. The original presentation was given by Patrick Thomson at C4[3] in September, 2009. Slides 68 and 69 were added by me for the PghRB talk.
Patrick's original slides are available at http://www.slideshare.net/importantshock/why-macruby-matters
1) The document discusses leveraging Modelica and FMI standards in Scilab open-source engineering software.
2) Key topics covered include Scilab use cases, integrating Modelica models into Scilab/Xcos, and using FMI for co-simulation and model exchange.
3) Demonstrations show automotive suspension modeling with Scilab/Xcos/Modelica, parameter identification in Xcos, and using FMI in Xcos for co-simulation.
This document provides an overview and summary of new features in Java 8. It begins with the schedule and release dates for Java 8 from 2012 to 2014. The major changes covered include lambda expressions, which allow passing code as data and are enabled by default functional interfaces. The new date/time API provides a modern replacement for the legacy Date/Calendar APIs. Type annotations allow adding metadata to types. Compact profiles define modular class libraries. Overall, Java 8 aims to better support parallel programming through new language features and library APIs.
The document discusses Scilab interface codes projects, including interfacing Scilab with languages like Ocaml, Tcl/Tk, Java, C++ and C. Notable areas for using Java with Scilab include numerical programming, text editors, graphics, Xcos and GUI. Recent research topics involving Scilab codes projects cover areas like gait recognition using 3D partial similarity matching, low rankness transfer for denoising, color guided depth map restoration, GPR signal processing for target recognition with circular antennas, and Urdu speech recognition using Hidden Markov models. Contact details are provided at the end.
MBrace is a programming model and cluster infrastructure for effectively defining and executing large scale computation in the cloud. Based on the .NET framework, it builds upon and extends F# asynchronous workflows.
https://skillsmatter.com/skillscasts/5157-mbrace-large-scale-distributed-computation-with-f
OrientDB uses Hazelcast to achieve a distributed configuration with multi-master replication. By using these together you can scale up horizontally by adding new servers without stopping or reconfigure the cluster. In this webinar, you’ll be introduced to OrientDB and how it compares to other NoSQL DBMS. You will also learn how and why Hazelcast is being used with OrientDB to achieve scale, elasticity and performance.
Both Hazelcast and Orient Technologies are providing professional open source support to their respective projects under the Apache software license.
Kineograph: Taking the Pulse of a Fast-Changing and Connected WorldQian Lin
Kineograph is a system for processing large-scale, time-sensitive graph data from continuous data streams. It uses an in-memory distributed graph storage and computation approach with three key aspects: 1) incremental graph mining on static snapshots to provide timeliness guarantees, 2) a graph partitioning scheme without locality considerations, 3) an epoch commit protocol using a progress table to ensure consistency during updates. It demonstrates the ability to incrementally compute graph algorithms like PageRank, shortest paths, and k-exposure on real-world Twitter graphs with millions of vertices and edges being updated at 100K per second.
1. The document discusses the design of a carry-ripple adder. It defines the generate, propagate, and kill functions used for each bit in the adder.
2. The carry for each bit is calculated by grouping the generate and propagate functions of lower order bits. The sum is calculated using the generate and propagate functions as well as the carry in.
3. The critical path in a carry-ripple adder goes through a chain of AND-OR gates rather than majority gates when using the grouped generate-propagate approach.
This document summarizes an approach for solving the train timetabling problem using a permutation-based evolutionary algorithm. It describes using a genetic algorithm with mutation operators that swap elements in the permutation representation. Constraints like minimum spacing between trains are handled by using a "kick" operator that removes conflicting trains from the schedule to resolve issues. Initial results on a large real-world problem showed the approach finding feasible solutions in 2/3 of cases and improving to always find solutions with more optimization.
This document contains a model examination for the subject Propulsion-II (Aeronautical Engineering) with questions in two parts - Part A and Part B.
Part A contains 10 multiple choice questions related to topics like impulse and reaction blades, turbine blade cooling, ramjet engine T-S diagram, components of pulse jet engine, applications of rocket propulsion, specific propellant consumption, types of propellant injectors, properties of liquid propellant, and thrust coefficient and nuclear propulsion.
Part B contains 5 long answer questions related to topics like lexical analyzer, transition diagrams, regular expressions, non-deterministic finite automata, deterministic finite automata, grammar, parsing tables, translation schemes, three address code, symbol
This document lists Matlab projects in three main categories: major Matlab features, domains for Matlab projects, and advanced modules for Matlab projects. Some of the key features and capabilities of Matlab mentioned include functions and data plotting, interfacing with other languages, user interface creation, and matrix manipulations. Notable domains listed for Matlab projects are embedded systems, surveillance/security, biomedical imaging, image processing, and neural networks/remote sensing. Specific advanced project modules listed include real-time fire detection, image hiding/cryptography, visual object tracking, and energy conservation using color coding.
https://github.com/leobenkel/Zparkio
Slides presented during the ScalaSF meetup on Thursday, March 26, 2020.
https://www.meetup.com/SF-Scala/events/268998404/
ZparkIO was on version 0.7.0 at the time, so things might be out of date.
Tailoring Redis Modules For Your Users’ NeedsRedis Labs
This document discusses using Redis modules to tailor Redis for users' needs. Redis modules allow adding new commands, data types, and APIs to Redis in order to make Redis understand custom data, speak custom languages, and do custom work. With modules, code can be consolidated across platforms, network hops minimized, and computation moved closer to data. The ReDe module is provided as an example of implementing an event dehydration algorithm in Redis using a module.
Since its first 1.12 release on July 2016, Docker Swarm Mode has matured enough as a clustering and scheduling tool for IT administrators and developers who can easily establish and manage a cluster of Docker nodes as a single virtual system. Swarm mode integrates the orchestration capabilities of Docker Swarm into Docker Engine itself and help administrators and developers with the ability to add or subtract container iterations as computing demands change. With sophisticated but easy to implement features like built-in Service Discovery, Routing Mesh, Secrets, declarative service model, scaling of the services, desired state reconciliation, scheduling, filters, multi-host networking model, Load-Balancing, rolling updates etc. Docker 17.06 is all set for production-ready product today. Join me webinar organised by Docker Izmir, to get familiar with the current Swarm Mode capabilities & functionalities across the heterogeneous environments.
MATLAB is a numerical computing environment and programming language developed in the 1970s. It was originally designed for matrix computations but has grown to include tools for data analysis, visualization, and GUI design. MATLAB allows both numeric calculations and programming and is commonly used in engineering, science, and mathematics applications. It includes toolboxes for tasks like signal processing, control systems, and computer vision.
This document discusses Matlab-based major projects for electrical and computer engineering (ECE). It lists the major domains supported for ECE projects as microelectronics, control systems, electrical energy and power systems, microwave and communication systems, and sensing, imaging and signal processing. It also describes hardware techniques like code generation, FPGA programming, and interfacing Matlab with other software. Finally, it provides examples of major ECE applications developed using Matlab like wireless motor control systems and solar tracking systems.
MBrace is a programming model and cluster infrastructure for large-scale distributed computing inspired by F# asynchronous workflows. It provides a declarative way to compose cloud computations using a monadic programming model. It runs on .NET and provides fault tolerance, elasticity, and multitasking capabilities. Performance tests on Azure showed MBrace can perform comparably to Hadoop for algorithms like distributed grep and k-means clustering.
This is a set of modified MacRuby presentation slides given at the Pittsburgh Ruby Brigade meeting on Nov 5, 2009. The original presentation was given by Patrick Thomson at C4[3] in September, 2009. Slides 68 and 69 were added by me for the PghRB talk.
Patrick's original slides are available at http://www.slideshare.net/importantshock/why-macruby-matters
1) The document discusses leveraging Modelica and FMI standards in Scilab open-source engineering software.
2) Key topics covered include Scilab use cases, integrating Modelica models into Scilab/Xcos, and using FMI for co-simulation and model exchange.
3) Demonstrations show automotive suspension modeling with Scilab/Xcos/Modelica, parameter identification in Xcos, and using FMI in Xcos for co-simulation.
This document provides an overview and summary of new features in Java 8. It begins with the schedule and release dates for Java 8 from 2012 to 2014. The major changes covered include lambda expressions, which allow passing code as data and are enabled by default functional interfaces. The new date/time API provides a modern replacement for the legacy Date/Calendar APIs. Type annotations allow adding metadata to types. Compact profiles define modular class libraries. Overall, Java 8 aims to better support parallel programming through new language features and library APIs.
The document discusses Scilab interface codes projects, including interfacing Scilab with languages like Ocaml, Tcl/Tk, Java, C++ and C. Notable areas for using Java with Scilab include numerical programming, text editors, graphics, Xcos and GUI. Recent research topics involving Scilab codes projects cover areas like gait recognition using 3D partial similarity matching, low rankness transfer for denoising, color guided depth map restoration, GPR signal processing for target recognition with circular antennas, and Urdu speech recognition using Hidden Markov models. Contact details are provided at the end.
MBrace is a programming model and cluster infrastructure for effectively defining and executing large scale computation in the cloud. Based on the .NET framework, it builds upon and extends F# asynchronous workflows.
https://skillsmatter.com/skillscasts/5157-mbrace-large-scale-distributed-computation-with-f
OrientDB uses Hazelcast to achieve a distributed configuration with multi-master replication. By using these together you can scale up horizontally by adding new servers without stopping or reconfigure the cluster. In this webinar, you’ll be introduced to OrientDB and how it compares to other NoSQL DBMS. You will also learn how and why Hazelcast is being used with OrientDB to achieve scale, elasticity and performance.
Both Hazelcast and Orient Technologies are providing professional open source support to their respective projects under the Apache software license.
MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming environment. MATLAB was originally designed for solving linear algebra problems using matrices but now has functions for data analysis, signal processing, optimization and other types of scientific computations. It also contains tools for 2D and 3D graphics. The MATLAB environment is command-oriented and includes a desktop, editor, debugger and other tools. It has a large library of mathematical and computational algorithms.
Build with Mbed - Exploring LoRa using MbedJan Jongboom
Webinar about the new LoRaWAN stack in Mbed OS 5.8, co-hosted with Etteplan. Recording: https://pages.arm.com/build-with-mbed-explore-LoRa-using-mbed.html
This document discusses WiFi network simulator projects and tools. It lists several popular network simulators like NS-3, OPNET, Omnet++ and Qualnet that can be used for WiFi network simulation projects in MATLAB. It then provides examples of recent research topics conducted using WiFi network simulators, including energy efficient load balancing between LTE and WiFi networks and jamming-resistant frequency hopping in cognitive WiFi networks. Finally, it outlines some channel estimation models used in WiFi network simulator projects, such as energy optimization with delay sensitive traffic and transmit power adaptation in WiFi mesh networks for rescue operations.
This document discusses different types of network simulators that can be used in MATLAB. It lists several open-source simulators like NS-2, NS-3, Omnet++ and proprietary simulators like Qualnet and Opnet. It also mentions some current research projects using network simulation in areas like supercomputer networks, isolated power systems, rumor routing protocols and wireless applications. Finally, it provides examples of modern research topics involving areas like smart grids, mobile network simulation, caching systems and taxi dispatching.
Scilab is a free and open source software that can be used to solve many numerical and technical problems with just a few lines of code. It contains hundreds of mathematical and simulation functions across major areas like control systems, digital signal processing, and bio medical image processing. Some recent research projects that have used Scilab include analyzing ECG signal denoising using discrete wavelet transforms and studying wireless energy transfer in fading relay channels. For any questions, users can contact the tutorial providers via their website or phone number provided.
This document discusses thesis writing support using MATLAB code. It lists major domains where MATLAB is used like pattern recognition, artificial intelligence, digital signal processing, and neural networks. It offers services like plagiarism checking, proofreading, writing the abstract and literature survey, and implementation support for theses involving MATLAB code. Students can contact the website or phone number listed for assistance with their MATLAB-based theses.
This document discusses Thesis MATLAB code support for medical image processing and various research topics. It provides examples of MATLAB code projects for object detection, video processing, food dietary assessment, retinal analysis, and lung analysis. Recent code projects cover topics like mitosis detection in breast cancer images using deep learning, breast imaging using differential microwave techniques, hyperspectral image classification using manifold geometry and domain adaptation, image quality assessment using extreme learning machines and NMF, and tampering localization in digital forensics using maximal entropy random walks. Contact information is provided for technical support.
This document provides information on various student MATLAB projects in areas such as image processing, network security, steganography, watermarking, and cryptography. It lists common image processing projects like image and audio enhancement, digital music, image and speech recognition, and medical imaging. The document also discusses artificial neural network projects using MATLAB, including projects on balancing angle and area distortions, optimizing bezigons for clipart images, cell migration reconstruction and visualization, multivariate time-varying data visualization, and perception and Hebbian learning. It provides contact information for the MATLAB project guides.
The document discusses source code for Matlab projects available on a website. It lists categories of source code like vectors, matrices, and graphical functions. It then provides examples of source code project topics like techniques for graph layouts and eye tracking data visualization. Further, it lists recent high-tech project topics involving areas like virtual environments, data projection, graph algorithms, flow visualization, and regression analysis. It concludes by providing contact details for the website.
This document discusses small Matlab projects in various areas including biometric authentication using techniques like lip-print, finger vein, iris, palm print, and fingerprint authentication. It also lists some latest research topics that these small Matlab projects could cover, such as RNA-seq data quantification, muscle force-length modeling, landslide displacement prediction, depth map upsampling, and steerable catheter classification. Major research fields supported by the small Matlab projects include functional brain mapping, smartphone localization, compressed sensing, technology node modeling, and medical knowledge base construction. Contact details are provided at the end.
Simple MATLAB Projects for Students Research AssistanceMatlab Simulation
This document discusses simple MATLAB projects for students using Simulink. It describes modeling support, customizable block libraries, graphical editors, and automatic code generation for simulating bioinformatics, mechatronics, and electronics. It also discusses real-time simulation, code generation, signal processing, wireless systems, control systems, and state-based modeling toolboxes in Simulink. Example project topics highlighted include pointing and steering tasks with low latency, unsupervised feature learning with geometry representations, digital multiplexing with cluster-dot screens, and region-aware 3D warping for digital image-based rendering.
Scilab is an open source software for numerical computation and data processing. This document outlines several Scilab toolboxes and functions, modern research topics using Scilab, recent Scilab video tutorial projects, and contact information. Key toolboxes mentioned include the Particle Swarm optimization toolbox, Signal acquisition and instrument toolbox, Metanet graphs and network flow toolbox, and Artificial Neural Network Toolbox. Recent Scilab video tutorial projects highlighted detect air gap eccentricity in induction motors, remote mobile robot path planning, and fault diagnosis for medium voltage induction motors. Contact details are provided to learn more about Scilab video tutorials.
This document provides information on Scilab tutorial videos, including their uses in areas like neural networks, data mining, and control systems. Recent Scilab video projects discussed involve caching images, noise removal for lung cancer diagnosis, and automated cell segmentation. The document ends with contact information for the website providing Scilab tutorial videos.
Scilab is an open source software for modeling, computing, and simulation. The tutorial discusses Scilab's interface XCOS which allows for building and editing models, submodeling for reuse, and customizing blocks and palettes. It also supports simulation, code generation, and result visualization. Additional functionality covered includes basic operations, control, signal processing, and plotting astronomical data. Major supported areas are listed as LMI optimization, control, animations, instrument modeling, aerospace modeling, and more. Contact information is provided at the end.
Scilab is an open source software for numerical computation and programming that provides help and support for domains including wireless sensor networks, wireless communication, data mining, signal processing, and image processing. It also offers major applications support for digital signal processing tasks such as adaptive filtering, waveform quantization and compression, linear and circular convolution, and multirate signal processing. Additionally, Scilab provides programming help for notable research areas including computation offloading frameworks, lossy image compression using SVD coding, vehicle detection and classification using audio visual cues, multi-temporal fusion of CT images for liver cancer diagnosis, Gaussian filtering of compressively sensed images, and region-based multi-focus image fusion using spectral parameter variance.
The document discusses Scilab programming help and commands. It provides an overview of common Scilab commands like names, ans, what, who, and clear. It also lists recent Scilab programming projects involving topics like surface reconstruction, image segmentation, image registration, blind source separation, and image classification. Contact information is provided at the end for any additional Scilab programming help.
This document provides information about Scilab program help including strong concepts, programming functions, and recent research topics in Scilab. Some strong concepts discussed are image compression using multilevel thresholding, motion deblurring from a single image, and spatial domain color image enhancement. Programming functions covered include solving differential equations, matrices and vectors, plotting, and variables. Recent research topics mentioned are constant SNR predictive lossy hyper spectral image compression, computer aided skin lesion detection, open biplanar MRI using inverse boundary element method, and synthetic aperture imaging with thinned linear sensor arrays. Contact details are provided at the end.
The document discusses Scilab support and services provided by www.matlabsimulation.com, including Scilab installation support for various versions on Windows, Linux and Mac OS, Scilab toolboxes that provide additional functionality, and topics covered under the Scilab help project such as signal processing, image processing, and applications in fields like ground penetrating radar and telecommunications. Contact details are provided at the end.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
2. Top Areas under Reed Solomon Code
Here are the list which developed under reed solomon matlab projects,
Wimax network Underwater acoustic
communication
Deep-space
telecommunication
Cloud storage system
Fog computing
Satellite
communication and
also broadcasting
3. Refined Functions of Reed Solomon Matlab Projects
The sophisticated functions of areas under reed solomon matlab projects are listed below,
comm.Differenti
alEncoder ()
vco () and also sinc ()
whdlFramesToSamples ()
demod ()
chirp () and diric ()
randerr () and also
randsrc ()
4. Approaches of Reed Solomon
Enumerate of the projects which used reed solomon matlab projects are noted,
Erasure code Kaneko
Trellis code
Convolutional
Chase
Berlekamp-
Massey