SPICE MODEL of LM7924 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7915 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7915 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7824 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7815 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7815 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7924 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7824 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7915 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7915 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7824 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7815 SIMetrix in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7815 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7924 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
SPICE MODEL of LM7824 PSpice in SPICE PARK. English Version is http://www.spicepark.net. Japanese Version is http://www.spicepark.com by Bee Technologies.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
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!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
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/
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Assure Contact Center Experiences for Your Customers With ThousandEyes
SPICE MODEL of LM7924 SIMetrix in SPICE PARK
1. Device Modeling Report
COMPONENTS: VOLTAGE REGULATOR
PART NUMBER: LM7924
MANUFACTURER: FAIRCHILD SEMICONDUCTOR
Panasonic
Bee Technologies Inc.
All Rights Reserved Copyright (c) Bee Technologies Inc. 2010
1
2. CIRCUIT CONFIGURATION
U1
LM7924
IN OUT
GND
MODEL PARAMETER
Model
Model description
parameter
VREF Reference Voltage
N Emission Coefficient
BETA Tranconductance of JFET Transistor
VAF Early Voltage of Output Pass Transistor
CPZ Output Impedance Zero Capacitor
RB2 Base Resistance of Output Limit Voltage Source
ESC1 Coefficient of Current Limit Voltage Source
ESC2 Coefficient of Current Limit Voltage Source
EFB1 Coefficient of Foldback Current Voltage Source
EFB2 Coefficient of Foldback Current Voltage Source
EFB3 Coefficient of Foldback Current Voltage Source
EB Non-ideal Base-Collector Diode Saturation Current
All Rights Reserved Copyright (c) Bee Technologies Inc. 2010
2
3. Input-Output Voltage Differential Characteristics
Simulation Result
0
-5
-10
OUTPUT / V
-15
-20
-25
-35 -30 -25 -20 -15 -10 -5 0
V1/V 5V/div
Evaluation Circuit
0 1A
V1 C1 C0 I1
2.2u 1u
GND OUTPUT
IN OUT
LM7924
U1
Comparison Table
Condition: IO = 1A, VI = -33V, CI = 2.2μF, CO = 1μF
Parameter Measurement Simulation %Error
VDROP (V) 2.000 2.043 2.15
All Rights Reserved Copyright (c) Bee Technologies Inc. 2010
3
4. Ripple Rejection (RR) Characteristics
Simulation Result
-28
U1-IN / V
-32
-36
-40
-23.992
OUTPUT / V
-23.996
-24
-24.004
-24.008
0 5 10 15 20 25 30 35 40
Time/mSecs 5mSecs/div
Evaluation Circuit
-33
V2
C1 C0
2.2u 1u 45
R1
AC 1 0 Sine(0 5 120 0 0)
V1
GND OUTPUT
IN OUT
LM7924
U1
Comparison Table
Condition: IO = 500mA, VI = 33V, CI = 2.2μF, CO = 1μF, f = 120Hz, ΔVI = 10V
Parameter Measurement Simulation %Error
RR(dB) 60.000 59.373 -1.04
All Rights Reserved Copyright (c) Bee Technologies Inc. 2010
4
5. Output Characteristics
Simulation Result
0
-5
-10
:OUT / V
-15
-20
-25
-30
-2.2 -2 -1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 -0
IRL/A 200mA/div
Evaluation Circuit
5 100Meg V=V(2,0)+V(3,0)
RL R2 B2
-33 2 3
V1 C1 C2 5 Pulse(10 50m 50m 500m 50n 50n 600m)
1 100Meg 100Meg 5 Pulse(0 100 0 50n 50n 50m 600m)
0.33uF 0.1uF V2
V=V(1,0)*(V(4, 0)-1) R3 R4 V3
B1
GND 4
IN IN OUT OUT
LM7924
U1
Comparison Table
Condition: IO = 250mA to 750mA, VI = 33V, CI = 2.2μF, CO = 1μF
Parameter Measurement Simulation %Error
VO(V) -24.000 -24.002 0.01
IPEAK(A) 2.200 2.183 -0.77
All Rights Reserved Copyright (c) Bee Technologies Inc. 2010
5