in this presentation content different types of interpolation formulas which is used for many applications,and give accurate answer of big calculation in short time.
Neural Network Back Propagation AlgorithmMartin Opdam
Explanation of the back propagation algorithm and gradient descent using a simple multilayer perceptron neural network.
The C# code for this example can be found on https://github.com/mpopdam/NeuraNet
MATHEMATICAL MODELING OF COMPLEX REDUNDANT SYSTEM UNDER HEAD-OF-LINE REPAIREditor IJMTER
Suppose a composite system consisting of two subsystems designated as ‘P’ and
‘Q’ connected in series. Subsystem ‘P’ consists of N non-identical units in series, while the
subsystem ‘Q’ consists of three identical components in parallel redundancy.
in this presentation content different types of interpolation formulas which is used for many applications,and give accurate answer of big calculation in short time.
Neural Network Back Propagation AlgorithmMartin Opdam
Explanation of the back propagation algorithm and gradient descent using a simple multilayer perceptron neural network.
The C# code for this example can be found on https://github.com/mpopdam/NeuraNet
MATHEMATICAL MODELING OF COMPLEX REDUNDANT SYSTEM UNDER HEAD-OF-LINE REPAIREditor IJMTER
Suppose a composite system consisting of two subsystems designated as ‘P’ and
‘Q’ connected in series. Subsystem ‘P’ consists of N non-identical units in series, while the
subsystem ‘Q’ consists of three identical components in parallel redundancy.
Umar Sidik
(BEng) Electrical and Electronic Engineering, Universitas Sumatera Utara, Indonesia
(MSc) Mechanical Engineering, National Defence University of Malaysia, Malaysia
Personal branding, la maîtrise parfaite de linkedinExtend Coaching
Le Personal Branding pour une maîtrise parfaite de Linkedin ou comment bien utiliser Linkedin
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Avec le Personal Branding, vous allez pouvoir vous décrire sur Linkedin de façon authentique et ciblée. L'objectif est de vous différentier des autres et de proposer une réelle expérience pour le lecteur.
Le Personal Branding est un processus de développement de marque personnel en 3 étapes: la découverte de la marque, la communique de celle-ci et finalement la vivre au jour le jour.
Martine Rainville – Le droit d’auteur appliqué aux blogues Made in
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Également, s’inspirer des autres, sans plagier : ou tracer la ligne ? Et quels sont les règles d’or à suivre.
Finalement, quels sont les recours légaux possibles dans le contexte où son blogue est plagié et où il y a violation du droit d’auteur ? C’est à toutes ces interrogations que Martine répondra lors de sa conférence.
ENGINEERING SYSTEM DYNAMICS-TAKE HOME ASSIGNMENT 2018musadoto
1. Read Chapter 4 – System Dynamics for Mechanical Engineers by Matthew Davies and Tony L. Schmitz and implement Examples 4.1 to 4.12 in Matlab.
2. Read Chapter 7 – System Dynamics for Mechanical Engineers by Matthew Davies and Tony L. Schmitz and implement Examples 7.1 to 7.11 in Matlab.
3. Read Chapter 9 – System Dynamics for Mechanical Engineers by Matthew Davies and Tony L. Schmitz and implement Examples 9.1 to 9.6 in Matlab.
4. Read Chapter 11 – System Dynamics for Mechanical Engineers by Matthew Davies and Tony L. Schmitz and implement Examples 11.1 to 11.7 in Matlab.
5. Read Chapter 2 - System Dynamics for Engineering Students: Concepts and Applications by Nicolae Lobontiu and attempt problem 2.18 (page 63).
6. Read Chapter 3 - System Dynamics for Engineering Students: Concepts and Applications by Nicolae Lobontiu and attempt problem 3.13 (pp 98 - 100).
7. Read Chapter 4 - System Dynamics for Engineering Students: Concepts and Applications by Nicolae Lobontiu and attempt problem 4.20 (page 146).
8. Read Chapter 5 - System Dynamics for Engineering Students: Concepts and Applications by Nicolae Lobontiu and attempt problems 5.15 (page 198), 5.21 (pp 199 - 200) and 5.27 (pp 201 – 202).
Fault modeling and parametric fault detection in analog VLSI circuits using d...IJECEIAES
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Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
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Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
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👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
1. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
1 | P a g e
The Impedance Matching in The Audio Signal Processing
Umar Sidik.BEng.MSc*
Director of Engineering
Electronusa Mechanical System (CTRONICS)
*umar.sidik@engineer.com
1. Introduction
Commonly, impedance is obstruction to transfer energy in the electronic circuit. Therefore, the
impedance matching is required to achieve the maximum power transfer. Furthermore, the
impedance matching equalizes the source impedance and load impedance. In other hand, the
emitter-follower (common-collector) provides the impedance matching delivered from the base
(input) to the emitter (output). The emitter-follower has high input resistance and low output
resistance. In the emitter-follower, the input resistance depends on the load resistance, while the
output resistance depends on the source resistance. In addition, this study implements the radial
electrolytic capacitor 100 25⁄ .
2. Analytical Work
In this study, and form the Thevenin voltage, while and deliver ac signal as and
(figure 1).
(a) (b)
Figure 1. (a). The concept of circuit analyzed in the study
(b). The equivalent circuit
2.1 Analysis of dc
First step, we have to calculate the Thevenin’s voltage in figure 1:
=
+
×
For this circuit, is 5 , then:
=
24 Ω
10 Ω + 24 Ω
× 5
24 Ω
34 Ω
× 5
= (0.71) × 5
= 3.55
2. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
2 | P a g e
Actually, in this circuit = , so = 3.55 .
The second step, we have to calculate :
= −
= 3.55 − 0.7
= 2.85
The third step, we have to calculate :
=
=
2.85
150Ω
= 19
2.2 Analysis of ac
In the analysis of ac, we involve the capacitor to pass the ac signal and we also involve the internal
resistance of emitter known as (figure 2).
(a) (b)
Figure 2. (a). The ac circuit
(b). The equivalent circuit for ac analysis
The first step, we have to calculate in the figure 2:
=
25
=
25
19
= 1.32Ω
The second step, we have to calculate ( ):
( ) = ( + 1) ( + )‖
( ) = (200 + 1) (150Ω + 8.2Ω)‖1.32Ω
3. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
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( ) = (201) (158.2Ω)‖1.32Ω
( ) = (201)
1
158.2Ω
+
1
1.32Ω
( ) = (201)
1.32
208.824Ω
+
158.2
208.824Ω
( ) = (201)
159.52
208.824Ω
( ) = (201)(0.764Ω)
( ) = 153.564Ω
The third step is to calculate :
=
( )
=
1
153.564Ω
= 0.0065
= 6.5
The fourth step is to calculate :
=
= (200)(0.0065 )
= 1.3
The last step is to calculate :
=
= (1.3 )(0.764Ω)
= 0.9932
= 993.2
3. Simulation Work
The simulation work can be classified into the dc analysis and the ac analysis.
3.1 Analysis of dc
In the simulation, is 3 (figure 3), while in the analytical work is 3.55 .
The different of the analytical work and the simulation work is:
(%) =
( ) − ( )
( )
× 100%
(%) =
3.55 − 3
3.55
× 100%
4. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
4 | P a g e
(%) =
0.55
3.55
× 100%
(%) = 18.33%
Figure 3. in the simulation
In the simulation, is 2.25 (figure 4), while in the analytical work is 2.85 . The different of the
analytical work and the simulation work is:
(%) =
( ) − ( )
( )
× 100%
(%) =
2.85 − 2.25
2.85
× 100%
(%) =
0.6
2.85
× 100%
(%) = 21.05%
Figure 4. in the simulation
In the simulation, is 15 (figure 5), while in the analytical work is 19 . The difference is:
(%) =
( ) − ( )
( )
× 100%
(%) =
19 − 15
19
× 100%
(%) =
4
19
× 100%
(%) = 21.05%
5. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
5 | P a g e
Figure 5. in the simulation
3.2 Analysis of ac
In the analytical is 6.5 (0.0065 ), while in the simulation is 0.07 (figure 6). The
difference is:
(%) =
( ) − ( )
( )
× 100%
(%) =
0.07 − 0.0065
0.07
× 100%
(%) =
0.0635
0.07
× 100%
(%) = 90.71%
(a) (b) (c)
(d) (e)
Figure 6. (a). in the simulation at 1Hz
(b). in the simulation at 10Hz
(c). in the simulation at 100Hz
(d). in the simulation at 1kHz
(e). in the simulation at 10kHz
6. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
6 | P a g e
In the simulation, is 14.9 (figure 7), while in the analytical is 1.3 . The difference is:
(%) =
( ) − ( )
( )
× 100%
(%) =
14.9 − 1.3
14.9
× 100%
(%) =
13.6
14.9
× 100%
(%) = 91.275%
(a) (b) (c)
(d) (e)
Figure 7. (a). in the simulation at 1Hz
(b). in the simulation at 10Hz
(c). in the simulation at 100Hz
(d). in the simulation at 1kHz
(e). in the simulation at 10kHz
In the simulation, is 0 at 1Hz, is 0 at 10Hz, is 0.05 at 100Hz, is 0.94 at 1kHz, 9.61 at
10kHz, and 15.2 at 16kHz (figure 8). The difference is:
For 1Hz,
(%) =
( ) − ( )
( )
× 100%
(%) =
1.3 − 0.53
1.3
× 100%
(%) =
1.30000 − 0.00053
1.3
× 100%
(%) =
1.29947
1.3
× 100%
(%) = 99.959%
8. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
8 | P a g e
(%) = 93.47%
For 16kHz,
(%) =
( ) − ( )
( )
× 100%
(%) =
1.3 − 84.8
1.3
× 100%
(%) =
1.3000 − 0.0848
1.3000
× 100%
(%) =
1.2152
1.3000
× 100%
(%) = 93.47%
(a) (b) (c)
(d) (e) (f)
Figure 8. (a). in the simulation at 1Hz
(b). in the simulation at 10Hz
(c). in the simulation at 100Hz
(d). in the simulation at 1kHz
(e). in the simulation at 10kHz
(f). in the simulation at 16kHz
In the simulation, is 0 at 1Hz, is 0 at 10Hz, is 0.32 at 100Hz, is 5.36 at 1kHz, is 53.8
at 10kHz, and 85.3 at 16kHz (figure 9). The difference is:
For 1Hz,
(%) =
( ) − ( )
( )
× 100%
(%) =
993.2 − 2.97
993.2
× 100%
(%) =
990.23
993.2
× 100%
(%) = 99.7%
10. Electronusa Mechanical System [Research Center for Electronic and Mechanical]
10 | P a g e
(%) = 52.17%
In this study, the simulation shows that the and became stable started at 1 kHz.
(a) (b) (c)
(d) (e) (f)
Figure 9. (a). in the simulation at 1Hz
(b). in the simulation at 10Hz
(c). in the simulation at 100Hz
(d). in the simulation at 1kHz
(e). in the simulation at 10kHz
(f). in the simulation at 16kHz