The document is a device modeling report for an operational amplifier (opamp), the NJM072D manufactured by New Japan Radio. It includes the component specifications, a description of the spice model, and the results of simulations comparing the model values to the datasheet specifications for parameters such as output voltage swing, input offset voltage, slew rate, input current, gain, and common mode rejection ratio. The simulations show good agreement with errors generally less than 1% compared to the datasheet values.
This document summarizes the simulation results of an operational amplifier component model. It tests parameters like output voltage swing, input offset voltage, slew rate, input current, open loop voltage gain, output short circuit current, and common mode rejection ratio. The simulation results show good agreement with the datasheet specifications, with most values matching within 2% error.
SPICE MODEL of PAT40-100T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
This document summarizes the simulation results of an operational amplifier component (NJM2068M) for key parameters including output voltage swing, input offset voltage, slew rate, input current, open loop voltage gain, and common mode rejection ratio. The simulation results are compared to the datasheet specifications and percent errors are reported to validate the accuracy of the SPICE model.
SPICE MODEL of PAT20-200T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of PAT250-32T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
The document is a device modeling report for an operational amplifier (opamp), the NJM072D manufactured by New Japan Radio. It includes the component specifications, a description of the spice model, and the results of simulations comparing the model values to the datasheet specifications for parameters such as output voltage swing, input offset voltage, slew rate, input current, gain, and common mode rejection ratio. The simulations show good agreement with errors generally less than 1% compared to the datasheet values.
This document summarizes the simulation results of an operational amplifier component model. It tests parameters like output voltage swing, input offset voltage, slew rate, input current, open loop voltage gain, output short circuit current, and common mode rejection ratio. The simulation results show good agreement with the datasheet specifications, with most values matching within 2% error.
SPICE MODEL of PAT40-100T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
This document summarizes the simulation results of an operational amplifier component (NJM2068M) for key parameters including output voltage swing, input offset voltage, slew rate, input current, open loop voltage gain, and common mode rejection ratio. The simulation results are compared to the datasheet specifications and percent errors are reported to validate the accuracy of the SPICE model.
SPICE MODEL of PAT20-200T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of PAT250-32T in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
This document summarizes the results of simulations run to characterize the performance of the NJM12902V operational amplifier made by New Japan Radio. The simulations analyzed key metrics such as output voltage swing, input offset voltage, slew rate, input bias current, open loop gain, output short circuit current, and common mode rejection ratio and found the simulation results matched well with the specifications in the manufacturer's datasheet.
The document is a device modeling report for an operational amplifier with part number NJM3403AV. It includes simulation results and comparisons to datasheet specifications for key amplifier parameters, including output voltage swing, input offset voltage, slew rate, input bias current, open loop gain, output short circuit current, and common mode rejection ratio. The simulations verify the operational amplifier behavior matches the expected datasheet specifications to within 5% error or less.
This document provides specifications and simulation results for an operational amplifier component, the NJM2716 manufactured by New Japan Radio. It examines the op amp's output voltage swing, input offset voltage, slew rate, input current, open loop voltage gain versus frequency, and common mode rejection ratio. The summary includes simulation results that closely match the manufacturer's published data sheet specifications.
Update 22 models(Schottky Rectifier ) in SPICE PARK(APR2024)Tsuyoshi Horigome
This document provides an inventory update of 6,747 parts at Spice Park as of April 2024. It lists the part numbers, manufacturers, and quantities of various semiconductor components, including 1,697 Schottky rectifier diodes from 29 different manufacturers. It also includes details on passive components, batteries, mechanical parts, motors, and lamps in the inventory.
The document provides an inventory update from April 2024 of the Spice Park collection which contains 6,747 electronic components. It includes tables listing the types of semiconductor components, passive parts, batteries, mechanical parts, motors, and lamps in the collection along with their manufacturer and quantities. One of the semiconductor components, the general purpose rectifier diode, is broken down into a more detailed table with 116 entries providing part numbers, manufacturers, thermal ratings, and remarks.
Update 31 models(Diode/General ) in SPICE PARK(MAR2024)Tsuyoshi Horigome
The document provides an inventory update from March 2024 of parts in the Spice Park warehouse. It lists 6,725 total parts across various categories including semiconductors, passive parts, batteries, mechanical parts, motors, and lamps. The semiconductor section lists 652 general purpose rectifier diodes from 18 different manufacturers with quantities ranging from 2 to 145 pieces.
This document provides an inventory list of parts at Spice Park as of March 2024. It contains 3 sections - Semiconductor parts (diodes, transistors, ICs etc.), Passive parts (capacitors, resistors etc.), and Battery parts. For Semiconductor parts, it lists 36 different part types and provides the quantity of each part. It then provides further details of Diode/General Purpose Rectifiers, listing the manufacturer and quantity of 652 individual part numbers.
Update 29 models(Solar cell) in SPICE PARK(FEB2024)Tsuyoshi Horigome
The document provides an inventory update from February 2024 of Spice Park, which contains 6,694 total pieces of electronic components and parts. It lists 36 categories of semiconductor devices, 11 categories of passive parts, 10 types of batteries, 5 mechanical parts, DC motors, lamps, and power supplies. It provides the most detailed listing for solar cells, with 1,003 total pieces from 51 manufacturers listed with part numbers.
The document provides an inventory update from February 2024 of Spice Park, which contains 6,694 electronic components. It lists the components by type (e.g. semiconductor), part number, manufacturer, thermal rating, and quantity on hand. For example, it shows that there are 621 general purpose rectifier diodes from manufacturers such as Fairchild, Fuji, Intersil, Rohm, Shindengen, and Toshiba. The detailed four-page section provides further information on the first item, general purpose rectifier diodes, including 152 individual part numbers and specifications.
This document discusses circuit simulations using LTspice. It describes driving a circuit simulation by inserting a 250 ohm resistor between the output terminals. It also describes simulating a 1 channel bridge circuit where the DUT1 and DUT2 resistors are both set to 100 ohms and the input voltage is set to either 1V or 5V.
This document discusses parametric sweeps of external and internal resistance values Rg for circuit simulation in LTspice. It also references outputting a waveform similar to a report on fall time characteristics for a device modeling report with customer Samsung.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
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.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Building Production Ready Search Pipelines with Spark and Milvus
SPICE MODEL of NJM062M in SPICE PARK
1. Device Modeling Report
COMPONENTS: OPERATIONAL AMPLIFIER
PART NUMBER: NJM062M
MANUFACTURER: NEW JAPAN RADIO
REMARK TYPE: (OPAMP)
Bee Technologies Inc.
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
2. Spice Model
OUT1 V+
-IN1 OUT2
+IN1 -IN2
V- +IN2
NJM062M_SUB
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
3. Output Voltage Swing, +Vout and –Vout
Simulation result
These simulation results are compared with +Vout
Evaluation circuit
Output Voltage Swing Data sheet Simulation %Error
+Vout(V) +14.2 +14.29 0.633
-Vout(V) -14 -14.09 0.642
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
4. Input Offset Voltage
Simulation result
Evaluation circuit
Measurement Simulation Error
Vos
15 mV 14.985 mV 0.1 %
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
5. Slew Rate, +SR, -SR
Simulation result
Evaluation circuit
Data sheet Simulation %Error
Slew Rate(v/us)
3.5V/us 3.475V/us 0.714
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
6. Input current Ib, Ibos
Simulation result
Evaluation circuit
Data sheet Simulation %Error
Ib(pA) 400 400.15 0.037
Ibos(pA) 200 200.06 0.03
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
7. Open Loop Voltage Gain vs. Frequency , Av-dc, f-0dB
Simulation result
Evaluation circuit
Data sheet Simulation %Error
f-0dB(MHz) 1 1
0
Av-dc 80 80.1 0.125
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004
8. Common-Mode Rejection Voltage gain
Simulation result
200mV
0V
-200mV
0s 1.0s 2.0s 3.0s 4.0s
V(Vout)
Time
Evaluation circuit
Vout U13
OUT1 V+
-IN1 OUT2
+IN1 -IN2
-14.985mVdc V- +IN2
V1 V+
NJM062_SUB
DC = 0 DC = 0
AC = 0 AC = 0
V- FREQ = 0 FREQ = 0 15Vdc
VAMPL = 0 Vi2 VAMPL = 0 Vin2
-15Vdc VOFF = 0 VOFF = 0
V
VOFF = 0
VAMPL = 0.5
FREQ = 1
AC = 0
DC = 0
0
Common Mode Reject Ratio=10115/0.275=36781
Data sheet Simulation %Error
CMRR
90 91.312 1.458
All Rights Reserved Copyright (c) Bee Technologies Inc. 2004