Satellite communications training course description This course starts by recaping some of the essential satellite knowledge required and proceeds to explore the deeper aspects of satellite communications, including hardware, communications and error control coding. What will you learn Explain how satellite communications work. Explain how RF works Explain the architecture of satellite systems. Use spectrum analysers. Satellite communications training course details Who will benefit: Anyone working with satellite systems. Prerequisites: None. Duration 3 days Satellite communications training course contents Basic Principles of Satellite Communications GEO, MEO and LEO satellites. Launching and orbits. Frequency bands and polarisation. Satellite footprints. Multibeam coverage. Power spectra. Link budgets. Modulation and coding. Access technologies. Earth station components. Space segment components. Satellite system services. Satellite operators. Radio frequency propagation Electromagnetic waves principles and generation. Reception of the EM wave. Space wave, sky wave and surface wave theory. The isotropic radiator. Types of antennae and their basic properties. Polar diagrams. International frequency allocation. Spectrum management and utilisation. Radio wave propagation. Line of sight propagation. Propagation for satellite comms. Free space path loss. Path attenuation. Noise and Interference. Power and its measurement. Satellite antennae and other hardware Power flux density. Effective aperture. Horn antennae. Parabolic reflector. Offset feed. Cassegrain and Gregorian antennae. Antenna feed systems - Horn, TMC, OMJ and polarizer. Antenna steering and mount systems. Array antennae. LNA, LNB, LNC. Microwave tubes - TWT and Klystron. Polarizers. Earth and Space Segments and the link Earth station antennae. Transponders. Antennae sub systems. Power supplies. Link budgets. System noise. System losses. Interference. Satellite switching. Ground Communications Equipment Baseband signals. Analogue and Digital systems. Overview of modulation - AM, FM, PM. Digital Modulation. Frequency conversion -up and down conversion. Filters, mixers, local oscillators, IF amplifiers and group delay equalisers. Access methods - single and multiple access systems. Data networks. Television transmission - analogue and digital. Digital signal compression. MPEG processing. Satellite Navigation Longitude, latitude, altitude, GPS, How GPS works, timing, alternatives to GPS. Mobile satellite services Voice and Phones, BGAN, TV, GPS to program aerial, VSAT. Error Control Coding The need for coding. Linear block codes. Cyclic codes. Convolution codes. Interleaving and concatenated codes. Coding gain. Turbo codes. Test and measurement Theory and practice of Spectrum Analysers.
Advanced Junos SP Routing course description This is designed to provide students with detailed coverage of OSPF, IS-IS, BGP, and routing policy. Students will gain experience in configuring, monitoring, and troubleshooting the Junos operating system and in monitoring device and protocol operations. This course uses Juniper Networks vMX Series Routers for the hands-on component, but the lab environment does not preclude the course from being applicable to other Juniper hardware platforms running the Junos OS. What will you learn Describe and configure OSPF area types and operations. Configure and monitor IS-IS. Describe basic BGP operation. Explain the causes for route instability. Describe how to troubleshoot routing policy. Explain the default behaviour of damping on links. Advanced Junos SP Routing course details Who will benefit: Network staff working with Junos at layer 3. Prerequisites: Junos Intermediate Routing Duration 5 days Advanced Junos SP Routing course contents OSPF OSPFv2 Review Link-State Advertisements Protocol Operations OSPF Authentication Lab: OSPF Multi-Area Networks Chapter 3: OSPF Areas Review of OSPF Areas Stub Area Operation and Configuration NSSA Operation and Configuration Route Summarization Lab: OSPF Route Summarization OSPF Case Studies and Solutions Virtual Links OSPF Multiarea Adjacencies External Reachability Lab: Advanced OSPF Options and Routing Policy Troubleshooting OSPF Troubleshooting OSPF Lab: OSPF Troubleshooting IS-IS Overview of IS-IS IS-IS PDUs Neighbors and Adjacencies Configuring and Monitoring IS-IS Lab: IS-IS Configuration and Monitoring Advanced IS-IS Operations and Configuration Options IS-IS Operations IS-IS Configuration Options IS-IS Routing Policy Lab: Advanced IS-IS Configuration Options and Routing Policy Multilevel IS-IS Networks Level 1 and Level 2 Operations Multilevel Configuration Lab: Configuring a Multilevel IS-IS Network Troubleshooting IS-IS Troubleshooting IS-IS Lab: IS-IS Troubleshooting BGP Review of BGP BGP Operations BGP Path Selection Options Configuration Options Lab: BGP and BGP Attributes BGP Attributes and Policy - Part1 BGP Policy Next Hop Origin and MED AS Path Lab: BGP Attributes - Next Hop, Origin, MED, and AS Path Attributes and Policy - Part2 Local Preference Communities Lab: BGP Attributes - Local Preference and Communities Route Reflection and Confederations Route Reflection Operation Configuration and Routing Knowledge BGP Confederations Lab: Scaling BGP BGP Route Damping Route Flap and Damping Overview Route Damping Parameters Configuring and Monitoring Route Damping Lab: BGP Route Damping Troubleshooting BGP Troubleshooting BGP Lab: BGP Troubleshooting Troubleshooting Policy Troubleshooting Policy Lab: Policy Troubleshooting
Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)
OOAD training course description A workshop course providing thorough practical knowledge of object oriented analysis and design methods. What will you learn Perform Systems Analysis with Object Oriented methods. Identify key classes and objects. Expand and refine OO problem domain models. Design Class hierarchies using inheritance and polymorphism. Design programs with Object Oriented methods. OOAD training course details Who will benefit: System analysts, designers, programmers and project managers. Prerequisites: It is desirable that delegates have experience of programming in C++/Java or some other OOP language. Duration 5 days OOAD training course contents What is OO? Classes, objects, messages, encapsulation, associations, inheritance, polymorphism, reusability. What is Systems Analysis and design? Data flow diagrams, structure diagrams. The OO approach. OOA The problem domain and object modelling. Identifying classes and objects. Generalisation and inheritance. Defining attributes and methods. OOD Refining the OOA results. Designing the User Interface. Designing the algorithms and data structures using objects. Designing the methods. OOP Prototyping. Implementing OOD with OOPs and OOPLs.
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Overview TQM is a completely structured, comprehensive, and organization-wide approach taken towards organisational structuring and management that continuously seeks to improve the quality rendered by the products, services belted out by the organization and the productivity of the resources handling the product. The aim is to continuously induce quality at each and every step of the organisational workflow in a bid to refine and fine- tune the processes and receive continuous feedback as per customers' norms to refine still further.
Overview The protocol is one of the most modern terms in terms of language but very old in terms of history as the word protocol is a development of the word of the conventions and understandings this is in the world of politics and at the international level, but within the field of business management has become the formulation of protocols is one of the important and necessary skills and very necessary for people who wish to They must take administrative duties. Through this course, we are going to introduce the rules and practices of gentle behaviour, the best practices for communication with others, and good reception, since all such related matters represent a large portion of our personality.
Overview Business modelling requires analysts to produce the quantitative models that top management uses to support their decision-making, but top management must also understand the strengths and weaknesses of the models if they are to use them effectively to support their decisions and robustly navigate the strategic negotiation landscape. This is particularly important for PPP projects where long-term commitments are made now based on bankability, value for money and risk allocation. During the course, participants will gain knowledge and skills on the frameworks, tools, and methodologies necessary to build quantitative models for financial decision-making in order to improve the financial viability and bankability of PPP projects. Participants will master modelling frameworks on capital budgeting, risk measurement, regression analysis and Monte Carlo Simulation among others.