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Symica is an electronic design automation tool for analog and mixed-signal integrated circuit design. It supports hierarchical design entry and compatibility with popular simulation models. Symica has capabilities for modern IC development including accommodating different process design kits. Its affordable and flexible pricing makes it attractive for startups and independent researchers. Established semiconductor companies can use Symica as a cost-saving solution for expanding design capabilities beyond limited licenses from major EDA vendors.
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The document discusses the operation and design tradeoffs of SAR and sigma-delta analog-to-digital converters (ADCs). It explains that SAR ADCs use a binary search approach to determine each output bit but are limited by noise and nonlinearity issues from components like track-and-hold switches and digital-to-analog converters. Sigma-delta ADCs shift quantization noise out of band through oversampling and noise shaping to achieve high resolution without requiring high-precision analog components. The document also covers speed limitations of SAR ADCs and how power consumption scales with resolution for different blocks like comparators and logic.
Cadence tutorial lab_2_f16
Lab 2: Cadence Tutorial on Layout and DRC/LVS/PEX
This section describes how to extract a netlist from your layout that includes parasitic resistances and capacitances. You will then be able to re-simulate your design with extracted parasitics in Spectre. PEX requires a clean LVS so that extracted parasitics can be correlated to nets on the schematic. Initiate the PEX interface by clicking on:Calibre > Run PEX
A window asking to load a runset file will now appear. Browse to the file
Step by step process of uploading presentation videos
Deep neural network, compressive sensing, floating gate techniques can be efficiently employed to increase voltage swing and reduce supply voltage requirements of class AB regulated cascode current mirrors, implement extreme low power analog circuits with this process. /also have good references for subthreshold region.
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This document is a project report submitted by Renu Gupta to fulfill requirements for a Master's degree in Electronics and Communication Engineering. The project involves realizing various signal processing and generating circuits using an Operational Trans-Resistance Amplifier (OTRA). The OTRA is implemented using commercially available CFOA ICs. Circuits designed include filters, oscillators, and an active inductor-based LC oscillator. Theoretical results are verified through PSPICE simulations and experiments using practical circuits assembled with CFOA ICs. The report documents the work conducted under the guidance of Dr. Neeta Pandey.
435601093 s-parameter LTtspice
S-parameters are used to analyze microwave circuits operating between 300MHz to 1000GHz. S-parameters relate the input and output traveling wave variables of network components using a scattering matrix. For a two-port network, the S-parameters relate the incident and reflected waves at each port. S11 and S22 represent reflection coefficients, while S12 and S21 represent transmission coefficients. Networks can be reciprocal if S12 = S21, and symmetrical if S11 = S22. LTSpice can be used to simulate S-parameters for two-port networks.
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Symica
Symica is an electronic design automation tool for analog and mixed-signal integrated circuit design. It supports hierarchical design entry and compatibility with popular simulation models. Symica has capabilities for modern IC development including accommodating different process design kits. Its affordable and flexible pricing makes it attractive for startups and independent researchers. Established semiconductor companies can use Symica as a cost-saving solution for expanding design capabilities beyond limited licenses from major EDA vendors.
Gene's law
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Tektronix mdo3104 mixed domain oscilloscope
The Tektronix MDO3104 is a mixed domain oscilloscope with 1 GHz analog bandwidth and built-in spectrum analyzer, arbitrary function generator, logic analyzer, and protocol analyzer. It offers 4 analog channels, 16 digital channels, and 1 RF input channel. The MDO3104 also supports a variety of serial protocols and comes with various optional application modules for extended analysis capabilities.
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The document discusses the operation and design tradeoffs of SAR and sigma-delta analog-to-digital converters (ADCs). It explains that SAR ADCs use a binary search approach to determine each output bit but are limited by noise and nonlinearity issues from components like track-and-hold switches and digital-to-analog converters. Sigma-delta ADCs shift quantization noise out of band through oversampling and noise shaping to achieve high resolution without requiring high-precision analog components. The document also covers speed limitations of SAR ADCs and how power consumption scales with resolution for different blocks like comparators and logic.
Cadence tutorial lab_2_f16
Lab 2: Cadence Tutorial on Layout and DRC/LVS/PEX
This section describes how to extract a netlist from your layout that includes parasitic resistances and capacitances. You will then be able to re-simulate your design with extracted parasitics in Spectre. PEX requires a clean LVS so that extracted parasitics can be correlated to nets on the schematic. Initiate the PEX interface by clicking on:Calibre > Run PEX
A window asking to load a runset file will now appear. Browse to the file
Step by step process of uploading presentation videos
Deep neural network, compressive sensing, floating gate techniques can be efficiently employed to increase voltage swing and reduce supply voltage requirements of class AB regulated cascode current mirrors, implement extreme low power analog circuits with this process. /also have good references for subthreshold region.
[Extreme Low Power Differential Pair: An Experimental Evaluation, Super-Gain-Boosted Miller Op-Amp based on Nested Regulated Cascode Techniques , Step by Step process of uploading presentation videos, Dennis Ritchie The creator of the C programming language and co-creator of Unix
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435601093 s-parameter LTtspice
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2. Key layers used in the layout are described, including Metal 1 (M1), Poly (PC), Diffusion (RX), Contact (CA), N-well (NW), P+ implant (BP), and Via 1 (V1). Design rules for spacing and dimensions are outlined.
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1. The document provides instructions on how to generate a layout view in Cadence Virtuoso and perform layout verification and simulation with extracted parasitics. It describes creating a CMOS inverter layout including placing nFET and pFET devices and connecting their terminals.
2. Key layers used in the layout are described, including Metal 1 (M1), Poly (PC), Diffusion (RX), Contact (CA), N-well (NW), P+ implant (BP), and Via 1 (V1). Design rules for spacing and dimensions are outlined.
3. An example inverter layout is shown, and instructions are provided on how to move and edit devices, enter layout shapes, and connect the devices to
Performance of the classification algorithm
The document discusses various performance evaluation metrics that are commonly used to evaluate classification algorithms and predictive models, including accuracy, precision, recall, F1 score, confusion matrix, receiver operating characteristic curve, and precision-recall curve. It provides definitions and formulas for calculating each of these metrics and discusses their strengths and weaknesses for evaluating model performance, especially for imbalanced datasets. Examples of each metric are given from literature on applications like seizure detection, trust prediction in social networks, and gene association networks. Feature extraction techniques for biomedical signals like EEG are also mentioned.
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#Abstract:
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- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
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- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
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Computational Engineering IITH Presentation
This Presentation will give you a brief idea about what Computational Engineering at IIT Hyderabad has to offer.
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